Methods of reducing consumption of energy and other resources associated with operating buildings

ABSTRACT

Methods for at least approximating any one or any combination of system targets of a) reducing the average energy expenditure for keeping at least one primary compartment of a building within a desired temperature range by means of active air conditioning, or b) reducing temperature variations during a typical 24-hour cycle within said at least one primary compartment of said building, or c) reducing one or both of the average temperature or the peak temperature of said at least one primary compartment of said building. Methods for at least partially increasing the typical lifetime of some components of buildings and thus reducing resources associated with maintaining at least some buildings function.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57.

BACKGROUND OF THE INVENTION Field of the Invention

One of the primary needs for the disclosed invention stems from thedesire to reduce energy consumption of buildings, which is a majorcontributor to global energy consumptions and thus indirectly to CO₂emissions.

The world's energy demand and consumption is rapidly growing, inparticular in developing countries. The finite amount of ultimatelyrecoverable fossil fuels (primarily coal, oil, gas), but moreimportantly the associated environmental pollutions and CO₂emissions—unsustainable at current rates,—as well as expected futureprice increases of energy from fossil resources make global energysupply one of the biggest challenge man kind faces.

Currently, the resources used for heating or cooling of buildingsconstitutes a major part of the total global energy (40%) and water(25%) consumption. Buildings are the source of nearly one third of thegreenhouse gas emission. Further details on this topic can be found, forexample, at UNEP. Sustainable buildings & climate initiative, buildingand climate change, United Nations Environment Program (2009), theentirety of which is incorporated herein by reference. During the periodof 1973-2010, the CO₂ emission was doubled (from 15.637 to 30,326million tons CO₂)

Further details on this topic can be found, for example, atInternational Energy Agency. Key world energy statistics. OECD/IEA(2012).http://www.iea.org/publications/freepublications/publication/kwes.pdf,the entirety of which is incorporated herein by reference. Therefore,buildings provide a substantial potential for reducing CO₂ emission (andoperating expenses) at relatively low cost, which is a concern primarilyin developed counties such as the USA or Europe. Simultaneously,advances in building materials, designs and system operations related toenergy consumption, if implemented on a large enough scale in developingcountries, can be a major contributor to at least slow down thecurrently occurring and often environmentally unacceptable (e.g. China)or even technically unsustainable (e.g. India) rate of required energysupply, in particular of electric energy, resulting from an constantlyincreasing standard of living for large portions of said populations.

The International Energy Agency (IEA) has published data on energyconsumption trends. While the total primary energy supply (TPES) wasdoubled from 1973 to 2010 (from 6107 to 12,717 million tons of oilequivalent, MTOE) and crude oil production increased almost 40% (from2869 to 4011 million tons), the total final energy consumption showed31% increase (from 2815 to 3691 MTOE).

The European Union's Energy Efficiency Directive (passed on 25 Oct.2012) recognizes that ‘ . . . the rate of building renovation needs tobe increased, as the existing building stock represents the singlebiggest potential sector for energy savings. Moreover, buildings arecrucial to achieving the Union's objective of reducing greenhouse gasemissions by 80-95% by 2050 compared to 1990’. Further details on thistopic can be found, for example, at Directive 2012/27/EU of the EuropeanParliament and of the Council of 25 Oct. 2012 on energy efficiency,amending Directives 2009/125/EC and 2010/30/EU and repealing Directives2004/8/EC and 2006/32/EChttp://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2012:315:0001:0056:EN:PDF,the entirety of which is incorporated herein by reference.

A related problematic aspect is the relative cost of energy. In most ofthe equatorial regions, where developing countries are predominantlylocated, the price for electricity compared to the average income is toohigh to permit 24/7 active air conditioning (AC) of most residential oroffice building. Therefore, any material, design, or systems controlimprovements to buildings, which will noticeably lower indoortemperatures and/or reduce required energy consumption of airconditioning, especially during dry seasons—i.e., during high solarradiation input, will considerably contribute to well-being andefficiency of its occupants.

Henceforth the term ‘supplied energy’ shall be understood to refer tothe energy delivered or supplied to a building (or similar space) onpurpose, typically produced elsewhere, and typically in form ofelectrical energy (regardless how it was generated, including but notlimited to being derived from chemical energy (typically fossil fuels),nuclear energy, mechanical kinetic energy (wind, water), orelectromagnetic (EM) wave energy in form of optical and/or IR solarirradiance, but explicitly also including electricity generated inphoto-voltaic cells mounted at least partially on the surface and/or inthe vicinity of said building). In some instances said supplied energymay at least in part be delivered to a building in form of chemicalenergy, in such cases typically as fossil fuels, but also e.g. in formof previously generated hydrogen or other generated chemicals, and theelectricity required to operate said air conditioning system isgenerated from said supplied chemical energy inside said building.

Thus, the term ‘supplied energy’ shall serve to distinguish it fromsources and types of energy involved in the discussed problem, namelyfrom solar energy in from of electromagnetic irradiance arriving at abuilding, thermal energy of the ambient air, thermal energy stored inthe structure of said building, it's components or dedicated energystorage systems, as well as in the air contained in said building etc.

Thus one of the primary need for the disclosed invention stems morespecifically from the desire to reduce the amount of supplied energyrequired to keep certain portions of buildings within certaintemperature ranges.

On of the secondary benefits of the disclosed invention is that in someembodiments it helps to reduce the consumption of other resources,namely building materials and labor. By at least approximating certainphysical and/or chemical target values within at least portion of saidpredominantly enclosed space, in some embodiments on average morefavorable conditions in terms of average temperature, humidity, and airthroughput (volume per time) can be achieved, which result in a higherlifetime of at least some components from which said predominantlyenclosed space is built. For example, in some such embodiments thelifetime of components made from wood or other organic materials can beincreased, and thus the time between repairs increased or the need forrepairs entirely eliminated.

One of the tertiary benefits of the disclosed invention is that itprovides means to supersede antiquated and unscientific building codesconcerning air flow in buildings, which are not based or derived fromoptimization or at least approximation of specific physical targetvalues.

Description of the Related Art

As explained in more technical detail further down, the thermal behaviorof a building is a classic example of a highly complexmultiphysics—problem, i.e. various physical effects determine—in acoupled manner—the energy budget (and thus temperature) as well asairflow inside and within the direct vicinity of a building.Specifically, actively driven and/or permitted or suppressed passive airflow within a building has a considerable effect on the energy budget ofa building. However, air flow in (at least parts of) buildings istypically not a primary design point, at least not with respect toresulting impact on the thermal budget of buildings, and if consideredat all overly simplifying approximations are frequently used, i.e. it isnot considered a fluid dynamic and aerodynamic problem.

Thus, there is a need for innovation to address aspects of air flow inat least parts of a building specifically targeted at reducing theaverage supplied energy expenditure for any one or any combination of a)keeping at least one primary compartment of a building within a desiredtemperature range by means of active air conditioning or heating, or b)reducing temperature variations during a typical 24-hour cycle withinsaid at least one primary compartment of said building, or c) reducingone or both of the average temperature or the peak temperature of saidat least one primary compartment of said building.

Secondly, throughout the most parts of the world, regulations and ruleshave been established, which govern certain technical aspects buildingconstructions, commonly referred to as building standards or buildingcodes. Clearly, the primary purpose is to ensure safety of occupants.Furthermore, such codes also govern requirements directly or indirectlyrelated to energy consumption, including but not limited to insulation,wall thicknesses, ventilation etc. In addition, some such codes concernrequirements related to esthetic aspects, i.e. the visual appearance ofbuildings.

It is noteworthy that within the United States of America, buildingcodes and standards adopted in numerous US states can all be traced backto a set of publications developed by at least one non-governmentfor-profit organization. Further details on this topic can be found, forexample, at “A Guide to California Housing Construction Codes”, State ofCalifornia, 2014 Department of Housing and Community Development,Division of Codes and Standards; “2013 California Building Code”,California Code of Regulations, Title 24, Part 2, Volume 1, CaliforniaBuilding Standards Commission, Sacramento, Calif. 95833-2936, ISBN:978-1-60983-457-9; “2013 California Building Code”, California Code ofRegulations, Title 24, Part 2, Volume 2, California Building StandardsCommission, Sacramento, Calif. 95833-2936, ISBN: 978-1-60983-457-9;“2013 California Residential Code”, California Code of Regulations,Title 24, Part 2.5, California Building Standards Commission,Sacramento, Calif. 95833-2936, ISBN: 978-1-60983-458-6; and Douglas W.Thornburg, John R. Henry: “2012 International Building Code Handbook”McGraw-Hill Education, LLC, New York 2012, ISBN 978-0-07-180131-7, theentirety of which are incorporated herein by reference.

While some aspects of these standards and codes are obviouslyindependent of geographic location—and thus climatic conditions—certainother aspects do considerably depend on typical environmental andclimatic conditions (temperatures, solar input, humidity, wind etc.) andthus these environmental aspects should be considered for establishingmeaningful and effective guidelines and codes for a given geographicregion. Yet this critical process of adjusting said standards and codeshas thus far not or only insufficiently occurred with respect to somespecific technical aspect. (In future, a better way how standards shouldbe defined is to make the definition independent of said environmentaland climatic conditions by not specifying specific shapes or sized, butby specifying specific desirable results.)

One specific such aspect expressed in these standards and codes relatesto ventilation, and more specifically one peculiar subsections concernsthe concept of a “net free vent area”, which will henceforth bediscussed in more detail.

For example, in the 2013 California Building Code, California Code ofRegulations, Title 24, Part 2, Volume 1, California Building StandardsCommission, the following formulation can be found: “Enclosed attics andenclosed rafter spaces formed where ceilings are applied directly to theunderside of roof framing members shall have cross ventilation for eachseparate space by ventilation openings protected against the entrance ofrain and snow. Blocking and bridging shall be arranged so as not tointerfere with the movement of air. An airspace of not less than . . .25 mm shall be provided between the insulation and the roof sheathing.The net free ventilating area shall not be less than 1/150th of the areaof the space ventilated”.

And furthermore: “Exterior openings into the attic space of any buildingintended for human occupancy shall be protected to prevent the entry ofbirds, squirrels, rodents, snakes and other similar creatures. Openingsfor ventilation having a least dimension of not less than . . . 1.6 mmand not more than . . . 6.4 mm shall be permitted. Openings forventilation having a least dimension larger than . . . 6.4 mm shall beprovided with corrosion-resistant wire cloth screening, hardware cloth,perforated vinyl or similar material with openings having a leastdimension of not less than . . . 1.6 mm) and not more than . . . 6.4mm.”

Comparable statements are made about under-floor ventilation. “Openingsfor under-floor ventilation: The net area of ventilation openings shallnot be less than . . . 0.67 m² for each 100 m² of crawl-space area.Ventilation openings shall be covered for their height and width withany of the following materials, provided that the least dimension of thecovering shall be not greater than . . . 6 mm.”

Thus, the seemingly magic ratio of 1:150 appears again. (In a fewinstances that ratio is inexplicably changed to 1:300, but theassociated fundamental problem remains.) This concept of a fixed “netfree vent area” (more accurately it should be call “vent area ratio”) isquestionable in terms of its technical utility based on at least 3 majorarguments:

1.) It Lacks Fundamental Technical or Scientific Rationale.

In order to be meaningful, any recommendations or standards expressed inrespect to required ventilation, or more accurately required air flow,an actual physical (or chemical) objective has to be defined, which byimplementation of said requirements one attempts to at leastapproximate. Ideally, specific minimal or maximal target values ofspecific physical or chemical quantities should be given. However,before mentioned concept of a “net free vent area” fails address anyfundamental physical objective. One may image, for example, that apossible target might be to maintain (or at least not to exceed) acertain level of humidity, a certain level of temperature, a certainamount of replaced air volume within a certain time frame, a certain airflow velocity, etc. all of which is entirely impossible to ensure in aconsistent manner for variably shaped buildings under hugely varyingclimatic conditions only with said trivial definition of a “net freevent area”.

2.) It Illustrated Fundamental Lack of Understanding Fluid Dynamics andAerodynamic Phenomena.

The manner in which requirements are expressed in the 2013 CaliforniaBuilding Code are effectively non-physical. First of all, based on thegiven definition, the term “net free ventilating area” is a misnomer,since it is the ratio of two areas, i.e. a dimensionless quantity and—ifused at all—should e.g. better be referred to as “ventilation arearatio”. Another ambiguity arises from the term “area of the spaceventilated”. It is not clear if this refers to the horizontal floor areaof the “space ventilated” or to the area of the roof (ceiling) abovesaid space (i.e., if it is indeed supposed to be a “ventilation inletarea to floor area ratio” or a “ventilation inlet area to roof arearatio”)

Secondly, either way, what is required is simply to surpass a certainratio (1:150) of two areas, presumably the sum of the area openings forventilation divided by presumably floor area. It is physically entirelyimpossible to make any meaningful predictions about the resulting airflow speed, spatial distribution, and throughput volume (i.e., athree-dimensional vector field) in an arbitrarily shaped attic witharbitrarily shaped and located openings solely based on such a singleratio. It is physically impossible that such a single simplistic rulecan ensure any specific physical target for different buildings andunder varying conditions. Without specifying at least the shape of thebuilding (including the attic, including any sub-spaces and divisions),thus also its volume, the number of openings, their cross section of allventilation openings, their shape, and size, the location where theopenings are placed, any (typically occurring) external air flow, thespatial orientation of the building with respect to such typicalexternal air flow, and furthermore any knowledge of thermally inducesflows (i.e. temperature profiles resulting in buoyancy and thusconvection) the actually occurring throughput of air can easily differseveral orders of magnitude, thus rendering the requirements such asthose expressed in the California Building Code, or other references,such as the 2012 International Building Code Handbook (Thornburg)physically and technically meaningless.

Such hugely simplified specification completely ignore the considerablephysical complexity of the underlying phenomena, in particular relatedthe fluid dynamics and thermal effects. More comments regarding thedifficulties of air flow predictions based (at least) on the governingNavier-Stokes equations (a system of nonlinear second order differentialequations of vector and scalar fields in three dimensions) will be givenfurther down.

3.) It Suffers from Lack of Consideration of Geographic and ThusMeteorological Variations.

Literally the same requirements to fulfill the “net free vent area”standards are being stated for California, District of Columbia, PuertoRico, New York (state), and Washington (state), to name a few. Thecorresponding phrases have been verbatim copied from [8], likely withoutany further technical review, which in some instances leads toincongruous requirements. For example, all standards, including the onesfor Florida and Puerto Rico, specify that “ventilation openings shall beprotected against rain and snow”. We believe that there is not a singleevent in recorded human history of naturally occurring snow in PuertoRico.

Thus, there is also a need for innovation to address aspects of air flowin buildings in a technically meaningful manner, which also provides anopportunity to achieve savings of various resources, namely in someinstances energy and/or materials, at least for certain building designsand under certain climatic conditions.

SUMMARY OF THE INVENTION

For purposes of summarizing the invention and the advantages achievedover the prior art, certain objects and advantages of the invention havebeen described herein. Of course, it is to be understood that notnecessarily all such objects or advantages may be achieved in accordancewith any particular embodiment of the invention. Thus, for example,those skilled in the art will recognize that the invention may beembodied or carried out in a manner that achieves or optimizes oneadvantage or group of advantages as taught herein without necessarilyachieving other objects or advantages as may be taught or suggestedherein.

The disclosed invention enables, among other applications, any one orany combination of

-   -   a) reducing the average supplied energy expenditure for keeping        at least one primary compartment of a building, typically        comprising at least one room, within a desired temperature range        by means of active air conditioning (or, although less typical,        in some instances heating), or    -   b) reducing temperature variations during a typical 24-hour        cycle (or multiples thereof) within said at least primary        compartment of said building, or    -   c) reducing one or both of the average temperature or the peak        temperature of said at least one primary compartment of said        building.

Furthermore, by reducing the supplied energy consumption also theoperating expenditure is reduced.

Obviously, such methods can not only be beneficially applied inequatorial, tropical, and subtropical regions, but also e.g. in areaslike the southwest of the Unites States, or central and southern partsof Europe during time of relatively high solar input.

The disclosed invention is at least in part based on a morecomprehensive understanding and consideration of the underlying coupledphysical effects, which describe the thermal and aerodynamic behavior(including energy budget) of buildings, and incorporating analytical,and/or numerical, and/or reduced order models thereof into advancedcontrol strategies, typically embodied in suitable electroniccontrollers, which can drive at least one adjustable element, henceforthreferred to as actuator (as more comprehensively defined below)installed in or on said building, which has directly or indirectlyimpact on said energy budget and/or air flow and/or other relatedphysical quantities including but not limited to a) temperature ortemperature variations, b) humidity or humidity variations, c) chemicalcomposition of air, i.e. oxygen levels (furthermore including level ofany organic or inorganic contamination), in at least parts of saidbuilding, and at least during certain time periods enabling alsoreductions of supplied energy (typically electrical energy) required tomaintain desired levels of such before mentioned physical and/orchemical quantities.

Thus, in the most general sense the disclosed invention serves in someembodiments to at least approximate a system target of

-   -   reducing the average expenditure of at least one resource within        one both of        -   at least one primary compartment of a building or        -   at least one secondary compartment of a building, and            said building being at least partially exposed to            directionally and temporally varying levels of solar            electromagnetic radiation as well as temporally varying            levels of air temperature,            said building comprising at least one primary compartment            and at least one secondary compartment, wherein said primary            compartment predominantly serves to achieve the primary            purpose of the building, and    -   wherein direct flow of air into and out of said primary        compartment is predominantly relatively restricted, and    -   wherein air can one or both of actively or passively be        exchanged between said secondary compartment and the outside of        said building,        furthermore comprising at least one electronic control system,    -   and said at least one control system being in communication with        -   at least one sensor to provide electronic signals            representing solar radiation levels,        -   at least one sensor to provide electronic signals            representing ambient air temperature levels,        -   at least one sensor to provide electronic signals            representing air temperature in said at least one secondary            compartment, and    -   said control system being able to one or any combination of        -   controlling means to modulate the throughput of passive air            flow to and from said at least secondary compartment,        -   controlling means to modulate the average speed of passive            air flow to and from said at least secondary compartment,        -   controlling means to modulate the throughput of actively            driven air flow to and from said at least secondary            compartment,        -   controlling means to modulate the average speed of actively            driven air flow to and from said at least secondary            compartment,    -   said control system further comprising at least one, at least        partially descriptive, reduced order model or simplified        discretized numerical model of the thermal behavior of said        building, and    -   said control system using said at least one reduced order model        or simplified discretized numerical model to derive control        signals suitable at least approximate said at least one system        target, and said control system having at least one data        interface to accept input of at least desired system target        values or types.

For example, an additional benefit of the disclosed invention is that insome embodiments it may also or exclusively serve to reduce theconsumption of resources such as building materials and labor. By atleast approximating certain physical and/or chemical target valueswithin at least portion of said predominantly enclosed space, in someembodiments on average more favorable conditions in terms of averagetemperature, humidity, and air (volume) throughput can be achieved,which result in a higher lifetime of at least some components from whichsaid predominantly enclosed space is built. For example, in some suchembodiments the lifetime of components made from wood can be increased,and thus the time between repairs increased or the need for repairsentirely eliminated.

Yet another benefit of the disclosed invention is that it can providemeans to supersede illogical building standards concerning air flow inbuildings, which are not based or derived from optimization or at leastapproximation of specific physical target quantities and values.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features, aspects, and advantages of the presentdisclosure are described with reference to the drawings of certainembodiments, which are intended to illustrate certain embodiments andnot to limit the invention.

FIG. 1 illustrates the spectral distribution of the spectral radiativeflux, i.e., spectral radiance, an ideal black body emits as a functionof wavelength, for four different temperatures.

FIG. 2 schematically illustrates a cross section of a buildingcomprising an internal space.

FIG. 3 schematically illustrates how ROM/SDNM is derived from arelatively high-fidelity numerical multi-physics model of the thermalbehavior of a building.

FIG. 4 schematically illustrates an embodiment of a building comparableto FIG. 2, with a different cross section.

FIGS. 5a and 5b schematically illustrate two different airflows in abuilding with a similar cross section as FIG. 4 with at least oneactuator in proximity to the ridge of the roof.

FIG. 6 schematically illustrates a building with a similar cross sectionas in FIGS. 5a and 5b , but with an additional secondary compartment.

FIG. 7 schematically illustrates a building with a similar cross sectionas in FIGS. 5a and 5b , but with two additional secondary compartmentspredominantly alongside the side walls of the building.

FIGS. 8a and 8b schematically illustrate buildings with a similar crosssection as in FIG. 7, but with an attic secondary compartment that formsa smaller space that is predominately located between an outer wall andan inner wall.

FIG. 9 schematically illustrates a building with a similar cross sectionas in FIGS. 8a and 8b , with an electronic controller.

DETAILED DESCRIPTION

FIG. 1 illustrates the spectral distribution of the spectral radiativeflux, i.e., spectral radiance, an ideal black body emits as a functionof wavelength, for four different temperatures, according to Planck'slaw. Also shown is the conceptual division of this part of theelectromagnetic spectrum in ultra-violet (UV), visible (VIS), NearInfrared (NIR), Mid Infrared (MIR), and Far Infrared (FIR).

By integrating Planck's law over all wavelengths Stefan-Boltzmann's lawcan be derived, which makes more apparent the (highly non-linear)correlation between the temperature and the total radiated. i.e. emittedpower density (per area), i.e. radiative flux or irradiance, of an idealblack body.

The lower the temperature of an object is, the more is the spectraldistribution of the emitted radiance shifted towards larger wavelength.The value of the wavelength where the spectral radiance has its maximumshall be denoted λ_(max). For example, at T=5780 K, the temperature ofthe surface of the sun, λ_(max)≈0.5 μm and the integrated spectralradiance reaches 63 MW/m². By integrating the spectral irradiance overthe corresponding wavelength ranges (and assuming ideal unfilteredblack-body radiation) one can derive that at this temperature of aradiating object, about 10% of the emitted radiation (i.e. emittedpower) is within the UV, 39% is visible to humans, 49% is within the NIRrange, and only about 2% within the MIR range.

To give another example, at T=1500 K the highest spectral irradiance isat λ_(max)≈1.93 μm. Already at this temperature (and of course lowerones) most of the emitted radiation is invisible to humans. In thisparticular example of T=1500 K, the amount of spectral irradiance at theupper wavelength limit visible to humans of about λ=0.7 μm, relative tothe maximum irradiance at λ_(max)≈1.93 μm is only about 2.5%. Again,integrated over the corresponding wavelength ranges one derives thatabout 0.05% of the emitted radiation is visible to humans, 56% is withinthe NIR range, and 44% within the MIR range.

At T=365.8 K=92.7° C. the integrated spectral radiance has dropped to 1kW/m² and the highest spectral irradiance is at λ_(max)≈8 μm. There isno radiation visible to humans, 0.08% of the emitted radiation is withinthe NIR range, and 98% within the MIR range.

At a typical room temperature of T=293.1 K=20° C. the maximum of thespectral radiance is at λ_(max)=9.9 μm. Here, about 97% the emittedradiation is within the MIR range, and 2.8% range within the FIR range.

This illustrates that (a) higher temperatures of an object,corresponding to shorter wavelength, nonlinearly higher power isradiatively transferred and that (b) the visual color and appearance ofan object can be considerably different from its thermal radiativebehavior.

At the bottom of FIG. 1 is a plot given, which shows the actual solarirradiance at the average distance between sun and earth, i.e. theirradiance outside earth' atmosphere, as well as the typical maximalirradiance at see level. This plot is based on the reference solarspectral irradiance ASTM G-173 [5]. As illustrated, most of the solarirradiance is contained in the wavelength range between 0.25 μm and 3.0μm. Integrated over the entire spectral range, the irradiance, whicharrives from the sun at the average distance between the sun and theearth (i.e., at the outer edge of the atmosphere) is approximately 1.36kW/m². Determined by the chemical composition and density of the air andfurthermore influenced by humidity (incl. clouds), dust, pollutionlevels, latitude, time of day, date, etc., the solar irradiance isattenuated while passing through the atmosphere and the spectrum isfiltered (some bands are suppressed). Under best-case conditions, thepeak levels of the irradiance at sea level is about 900 W/m².

The solar irradiance, which arrives at sea level after passing throughearth' atmosphere, now comprises only about <4% within the UV range,about 45% within the VIS range, and 51% in the NIR range (more preciselybetween 750 nm and 2.5 μm). These ratios are good approximates. Moreprecise values depend on numerous other parameters.

These plots also illustrate that solar radiation can in first orderstill be approximated as black body radiation.

As an additional reference it shall be commented, that in the southwestof the United States, at ground level, the average energy density perday on a horizontal plate is about 5 to 6 kWh/m²/day on a horizontalplate (e.g. a horizontal surface of a building) and >9 kWh/m²/day on asurface, which is 2-axis tracking to remain normal to the incidence(Source: National Solar Radiation Data Base).

Said solar irradiance is one of the sources of thermal gains of abuilding, which needs to be considered for the subsequently describedcomputation and prediction of the thermal budget of a building.Furthermore, buildings can lower their thermal budget by emittingradiation in the MIR range, if external conditions permit (i.e. toward aclear night sky).

A second source of thermal gains or losses of a building is due toconvection as a result of contact with an external flow field of air.

FIG. 2 illustrates highly schematically and not to scale a cross sectionof a building comprising an internal space 200, which is divided intoprimary compartments 2001 and 2002 and wherein said primary compartmentspredominantly serve to achieve the primary purpose of the building suchas for example living space for humans or animals, office space,equipment space (e.g. computers incl. server farms etc. or othermachinery), or storage spaces. Furthermore denoted is the airtemperature field _(air)T(r, t)_(int-p), (bold letters representingvectors), present in said primary compartments. The internal space ispredominantly defined by walls 201, which may also comprise windows,doors, and other openings, schematically represented as 202. The directflow of air into and out of said primary compartments is predominantlyrelatively restricted. There is also at least one secondary compartment,here illustrated as secondary compartment 2031 and 2032, at leastpartially defined by walls 204 as well as walls 201. It shall be notedthat the subsequently disclosed inventions is not dependent on thechoice of materials used for said walls, although this has of courseimpact on the heat capacity of the building (and thus thermal energystored in the structure), thermal conductivity, and time constants.

The building is exposed to a temporally and spatially varying externalair flow field 205 with the air velocity vector field denoted as_(air)v(r, t)_(ext) and air temperature scalar field denoted _(air)T(r,t)_(ext). The dotted arrows used to indicate the air flow field (bothinside and outside said building) are only meant to illustrate the airflow in principle, but are not to be understood to representrepresentations of actual computational fluid dynamics (CFD) simulationsor measurements.

Furthermore, the building is exposed to directionally and temporallyvarying levels of solar electromagnetic radiation (or irradiance) 206,roughly resembling atmospherically filtered black body radiation ofapproximately 5600 K, as discussed above.

Said at least on secondary compartment comprises at least one, buttypically a plurality of typically electrically controlled actuators207, which can any one or any combination of

-   -   modulate the amount of passive air flow to and/or from said at        least one secondary compartment, and/or    -   actively drive air flow to and/or from said at least one        secondary compartment at a controllable rate, and/or    -   or modulate the amount of otherwise actively driven air flow to        and/or from said at least one secondary compartment.

Thus, in the context of this invention the term “actuator” 207 shall beunderstood to define at least one class of devices, which can achievesaid functions, including but not limited to a any one or anycombination of typically electrically driven and/or controlled: variablevalves, shutters, gates, choke point, or other variable restrictions;propelled fans of any shape and/or any other moving configuration (e.g.also including but not limited to axial fans, centrifugal fans,impellors, blowers, other pumps, and also including those, which arepredominantly not rotating e.g. incl. bellows, paddles, etc.) or anyarrangement suitable to affect, drive, or suppress air flow at avariable rate and/or direction. Variable shall mean to have at least twostates (such as on and off, or full on and ½ on, inward or outward,etc.), i.e. a pulse-width modulated control scheme shall explicitly beincluded, but in many embodiments said actuators 207 will be able toassume a plurality of discrete states, typically dictated by the bitwidth of the underlying control circuitry (e.g. 4 bit, 8 bit, 10 bit, 12bit, etc. . . . ) and/or design of stepper motors etc.), or in someinstances said actuator may be able to be controlled in an analog mode.

Furthermore distributed throughout the inside of said building, and/orin or on its walls, and/or on the outside of said building, and/or inits immediate vicinity is a plurality of sensors 208, which provideelectronic representation (readout) of any one or any combination ofphysical quantities:

-   -   air temperature,    -   air flow speed, and/or mass flow rate    -   air flow directions (i.e., vector information)    -   air pressure    -   air humidity    -   electromagnetic spectral information in the IR and/or VIS range,    -   either as 0-, 1-, or 2-dimensional sensor,    -   resulting from any one or any combination of solar radiation,        reflection of solar radiation from the environment, or being        emitted from walls of said building.

(In some instances also indirectly derived turbulence data, e.g.Reynolds numbers may be included, i.e., considered input from“sensors”.)

Said sensors 208 provide sensor data to an “electronic control system”,henceforth also referred to as “control system” or “electroniccontroller” 209. In typical embodiments said control system comprises atleast one processing unit 2091, which may further comprise a pluralityof analog and/or digital I/O boards, some of which send signals toand/or receive signals from, and/or provide power to said plurality ofsensors 208, and some of said I/O boards send signals to and/or receivesignals from, and/or provide power to and/or otherwise drive saidactuators 207, thus for example affecting the air flow speed and/or airthroughput. (The terms “performance of said control system” and “controlsystem performance” are henceforth considered to be synonymous.)

For digital signals this may in some embodiments comprise standards suchas RS232, RS485, RS422, GPIB, LonWorks, SCADA, CAN, CANopen, Profibus,SafetyBUS, INTERBUS, SERCOS, Sinec H1, Ethernet, EtherCAT, LXI (LANeXtensions for Instrumentation) and all other Ethernet basedcommunications systems or other types of networks and field buses, someof which are listed further down.

In some embodiments some signal lines from/to said plurality of analogand/or digital I/O boards may be directly connected to said a pluralityof sensors 208, and actuators 207, while some other signals may have toundergo amplification, filtering, conversion, or other processing inadditional electronic components 2092. This may in some embodimentscomprise, power amplifiers, driver motors, incl. for stepper motors,signal modulators/demodulators etc.

In some embodiment the communication between said at least oneelectronic controller 209, including said additional electroniccomponents 2092, and at least some of sensors 2081 and/or actuators 2071are at least in part based on wireless transmissions, including variouswireless standards and/or protocols, in particular any type of medium orhigher rate wireless personal area network, which in many instances mayalready be present in many buildings, including but not limited to thosebased all variants of IEEE 802.11 (“Wi-Fi”), IEEE 802.16m (“WiMAX”),and/or any other TCP/IP (IPv4 and/or IPv6) based local wirelessnetworks, and/or any derived versions thereof, or other futurecomparable standards and/or protocols.

The processing unit 2091 may be based on any one or any combination ofsuitable computational architecture, incl. for example x86, x86-64, ARM,etc., incl. also any embedded systems, furthermore any so called “systemon a chip” (SoC) e.g. Snapdragon, and may in some embodiments at leastpartially also comprise FPGAs and/or PLCs. The chassis and/or busstructure of said processing unit 2091 may in some embodiments be basedon PCI, PXI, PXIe.

In some embodiments said at least one electronic controller 209 is alsoexecuting an at least one algorithm, either entirely in software and/orat least partially in hardware (e.g. in FPGAs), which at least in partserves to at least approximate any one or any combination of systemtargets of

-   -   reducing the average energy expenditure for keeping at least one        primary compartment of a building within a desired temperature        range by means of active air conditioning,    -   or    -   reducing temperature variations during a typical 24-hour cycle    -   within said at least one primary compartment of said building,    -   or    -   reducing one or both of the average temperature or the peak        temperature    -   of said at least one primary compartment of said building.

Said at least one algorithm executed by said controller 209 at least inpart comprises an at least partially descriptive, reduced order model(ROM) and/or simplified discrete numerical model (SDNM) 2093 of thethermal behavior of said building, which in some embodiments at leastenables to at least approximately compute the thermal budget of saidbuilding (i.e., in particular the stored thermal energy) as well asspatial air and wall temperature distribution.

As input values to said at least one model serve at least the measuredsensory data _(m)M_(t) acquired at time t. Thus _(m)M_(t) can be thoughtof as a long vector comprising all quantities acquired by all sensors(including the scalar components of any acquired 3D vectors, such asflow directions or directional information of incident solarirradiance), although in some cases said algorithm may not use all ofthem. In some embodiments at least some sensor date_(m)M_((t-n·dt), . . . (t−dt)), which were previously acquired at one ora certain number n of time steps dt may be used as additional data inputvectors. In some embodiments at least some sensor date_(p)M_((t+dt), . . . (t+n·dt)), which are predicted to occur at one or acertain number n of future time steps dt may be used as additional datainput vectors. This may in many cases concern predicted environmentalconditions such as predicted external air flow speed and air temperatureas well as incident solar irradiance and direction thereof. In someembodiments such data may be obtained from external data sources such asweather forecasting entities, and in many embodiments such data istransmitted to said controller 209 via the internet. In some embodimentssaid controller 209 may also execute at least rudimentary predictivecalculations itself, specifically concerning solar directionalinformation.

Said reduced order model (ROM) and/or simplified discrete numericalmodel (SDNM) enables in particular to calculate at least in part and atleast approximately what shall henceforth be referred to as the thermalsystem state S_(t) (or thermal budget) of said building at a given timet as well as at one or a certain number n of future time steps dt. Saidstate S_(t) shall at least comprise temperatures of components of thebuilding (e.g. walls) at various points, air temperature at variouspoints at least inside said primary compartments. In addition, saidROM/SDNM model provides at least approximate values for the total storedthermal energy Q_(t) (primarily as result of its thermal mass, i.e.spatial distribution of heat capacity), and in some embodiments also ina spatially resolved manner, i.e. how the thermal energy is spatiallydistributed in the structure Q_(t) (r).

Furthermore, said model is thus able to predict the temperature responseas a result of removed or gained thermal energy, in particular as aresult of any one and any combination of

-   -   a) environmental conditions at least comprising    -   external airflow and the resulting convective thermal gains or        losses,    -   radiative gains from solar irradiance and radiative losses if        the surfaces of said building can emit toward colder        surroundings (e.g. the night sky),    -   b) induced air flow (outside and/or inside said building) as a        result of thermal gradients (both as a result of radiative gains        or other internal sources) and resulting redistribution of        energy as well as resulting thermal gains or losses,    -   c) by means of said actuators 207 modulated passive air flow or        actively driven air flow inside said building, in particular        modulated air flow in said secondary compartments, as well as    -   d) actively powered (by “supplied energy” as defined above)        internal sources or sinks of energy such as air conditioning        systems, heaters etc., as well as unintentional sources of        energy input (e.g. cooking ovens).

Thus said algorithm uses said ROM/SDNM to evaluate a plurality ofscenarios of possible control strategies ahead of time in order to findat least one or several which reduces, in some cases minimizes,consumption of supplied energy (as defined above), i.e. electricalenergy spent for active air condition systems, in particular by beingable to make predictions how air flow into and/or out of and/or withinsaid secondary compartments influences the thermal budget of saidbuilding and affects the temperature in at least one of said primarycompartments.

Fundamentally, the ability to achieve at least in some cases and duringcertain times and conditions any such reduction of supplied energyconsumptions is the result of the fact that said modulation of air flowby actuators 207 will typically require less energy to achieve a certaincontrol target (e.g. a temperature in said at least one primarycompartment) compared to exclusively using actively powered air systems,but provided that the employed ROM/SDNM is of sufficient fidelity, i.e.predictive value.

Thus said at least one controller 209 uses said at least one ROM/SDNM toderive control signals suitable at least approximate said at least onesystem target by repeatedly running and comparing the effectiveness ofvarious such strategies.

FIG. 3 illustrates highly schematically how said ROM/SDNM is derivedfrom what will henceforth be referred to as a (relatively) high-fidelitynumerical multi-physics model (HFNM) of the thermal behavior of saidbuilding.

The thermal behavior or the thermal budget of predominantly enclosedspaces, such as buildings or similar habitats, is a classic example of ahighly complex multi-physics-problem, i.e., a problem where numerousdifferent physical effects or phenomena play a role in a coupled manner,i.e., simply put, in general the results of (any) one effect will haveimpact on the degree to which (any) another effect plays a role. Assuch, related (coupled) to the energy budget of a building are thetemperature distribution in the structure of said building, as well asair flow (speed, direction), temperature and humidity inside and withinthe direct vicinity of said building.

As explained in more detail further below, in order to describe saidthermal behavior, time-dependent solutions to very large systems ofcoupled differential equations are required. However, it is effectivelyimpossible to find any direct analytical solution for these equationsfor any realistic 3D geometry (finite size, no or weak symmetry).Therefore, an accurate (“high-fidelity”) analysis (prediction) of thethermal behavior of a building must be based on numerical models andnumerical solution methods to solve the underlying coupled differentialequations of a discretized model of at least one given building and itsinteraction with the environment, i.e., at least in some cases at leastpart of the environment may be part of the discretized model.

The more, typically coupled, physical effects are incorporated into amathematical model, and the better (more accurately) material constants(or functions) are known, the more precisely the model can predict thethermal behavior of the described building. Such models consist, atleast conceptually, out of a potentially large set of coupleddifferential equations and non-differential equations.

Creating such discretized models and obtaining the correspondingsolutions is difficult and computationally highly demanding, butpossible. In particular, typically any one or any combination of thefollowing numerical methods is used to generate said HFNM: FiniteElement Method (FEM), Finite Difference Method (FDM), Finite VolumeMethod (FVM), Finite Difference Time Domain (FDTD). Monte Carlo Method,Boundary Element Method (BEM), including any sub-variant of any of theabove, often also in combination with iterative methods, including butnot limited to successive approximations. Some such methods aremesh-based (e.g. FEM), others are not (e.g. BEM).

The optimal choice of the particular numerical method or combinationsthereof depends on the specific case and on the desired level offidelity.

As input data for the HFNM will typically be required at least

-   -   the 3d spatial geometry of the building (i.e., shape of all        structural and other elements)    -   thus also providing the enclosed air volumes,    -   the 3d spatial distribution of heat capacity of materials which        constitute a building    -   (enabeling also to compute the total heat capacity of a building        materials)    -   the 3d spatial distribution of thermal conductance (of bulk        material, including windows)    -   in a building    -   the 3d spatial distribution of specific spectral electromagnetic        properties    -   (typically UV to FIR reflectivity) of bulk materials and        surfaces in a building    -   the 3d spatial distribution of spectral electromagnetic        properties transmission of any    -   windows (i.e., transmittance/reflectance as function of        wavelength)    -   if present, the spatial distribution of phase change materials        within a building and the corresponding phase transition        enthalpies    -   if present, location, size, and parameters of other energy        sources or sinks (e.g. AC)    -   if present, location, size, and parameters of actively driven        air.

As a next step typically at least one solid model is generatednumerically describing the spatial arrangements of all componentsconsidered in the HFNM.

As a next step spatial and temporal discretization levels are chosen forthe subsequent numerical computations. In many embodiments choosingspatial discretization will for example imply defining the element size(in case of FEM) at various locations within the model, which needs tobe known in the subsequent step involving meshing said solid model. Insome embodiments choosing temporal discretization will for example implydefining the time step size to be used when computing time dependentphenomena.

The degree of spatial and temporal discretization has considerableimpact on the accuracy of the computed result (or if a result can beobtained at all). In general, the finer the discretization, the higherthe accuracy of the result, but also the higher the computationaleffort. This is in particular a consideration for 3d models, wheredoubling linear spatial resolution results approximately 8-timers highernumber of the resulting degrees of freedom on case of FEM models. Toprovide a very crude example, if a hypothetical building where to beapproximated as a (10 m)³ cube and the uniform spatial resolution wouldbe 10 cm, solving for a single scalar degree of freedom on each nodepoint (e.g. only temperature for a heat conductance problem) wouldresult in approximately 100³=10⁶ nodes (assuming linear elements), i.e.about 1 million unknowns (typically represented as at least 4 bytesingle precision, but typically 8 byte double precision variables) to beobtained as solution from a sparse system of equations. However, 10 cmdiscretization is relatively course compared to the typical features ofa house (e.g. compared to wall thickness.) If the spatial discretizationwere to be refined to 1 cm, the result would be approximately 10⁹ nodepoints, i.e., approximately 1 billion unknowns. Moreover, a realisticmultiphysics simulation will simultaneously solve for several physicalquantities at a single node point (assuming the same mesh is used), forexample, air flow speed vectors, air pressure, etc.

This illustrates the importance of skillful creation of the HFNM(balancing computational effort with accuracy. It furthermoredemonstrates as essential for the disclosed invention the need to usecomputationally orders of magnitude less expensive ROMs/SDNMs in saidcontrol system 209, which typically has orders of magnitude lesscomputational power than typical high-end workstations or even computeclusters used to solve the underlying HFNM.

However, the consistently increasing performance of computationalhardware (e.g. the availability of workstations with 32 processor coresand 128 Gbyte main memory as of 2017) has now moved it in the realm ofpractical possibilities to obtain solutions to such HFNM with acceptablefinancial effort (i.e., without using super computers).

As illustrated in FIG. 3, as a next step a set of boundary and initialconditions is chosen for the subsequent computation. While some of thedata required to generate the ROM/SDNM can be obtained with a singlesolution of said HFNM (e.g. computation of total heat capacity), otherswill require several solution under changing boundary and initialconditions, for example changing directions external air flow fields aswell as changing directions of solar irradiance.

The solution data obtained in the step above are now being used togenerate and refine said ROM/SDNM. The process of obtaining solutions tothe HFNM is in some embodiments repeated in an iterative manner untilthe ROM/SDNM reaches an acceptable level of accuracy compared to theHFNM. It is helpful during this step to know the location of saidsensors 208 and 2081 as well as said actuators 207 and 2071 and type ofinput data, since ultimately these data are the once which the ROM/SDNMwill be given during future practical application to derive its controlstrategy from. Conversely, said iterative process can also serve to finddesirable locations for said sensors and/or actuators. In other words,the measured sensory data _(m)M_(t), which form the input data for saidROM/SDNM, can be considered to cover relatively high-dimensional(parameter) space, and for each specific vector _(m)M_(t) represents aspecific state of internal and external conditions within this space,and for which the ROM/SDNM must at least be able to provide the thermalsystem state S_(t) (or thermal budget) of said building (and the totalstored thermal energy Q_(t)) within a certain error margin.

As mentioned, said state S_(t) shall at least comprise temperatures ofcomponents of the building (e.g. walls) at various points, and airtemperatures at various points at least inside said primarycompartments.

FIG. 4 is comparable to FIG. 1 and illustrates highly schematically andnot to scale an embodiment of the disclosed invention on a building witha different cross section, here a type of gable roof (regardless ofactual pitch), forming a secondary compartment 4031, here predominantlyan attic space, and actuators 207 in proximity to the eaves. Again,distributed throughout the inside of said building, and/or in or on itswalls, and/or on the outside of said building, and/or in its immediatevicinity is a plurality of sensors 208, including in some versions ofthis embodiment sensor 2081 with wireless data communication.

FIG. 5 is comparable to FIG. 4 and illustrates highly schematically andnot to scale a similar embodiment of the disclosed invention of abuilding with a similar cross section as in FIG. 4, here a type of gableroof (regardless of actual pitch), with at least one, but typically aplurality of actuators 207 in proximity to the ridge of the roof. Again,distributed throughout the inside of said building, and/or in or on itswalls, and/or on the outside of said building, and/or in its immediatevicinity is a plurality of sensors 208, including in some versions ofthis embodiment sensor 2081 with wireless data communication. Saidelectronic controller 209 has been omitted in this figure.

FIG. 5a (top) illustrates one mode of operation, whereby the airflow insaid secondary compartment 4031, here predominantly an attic space, ispredominantly from the ridge of the roof towards the eaves. FIG. 5b(bottom) illustrates one mode of operation, whereby the airflow in saidsecondary compartment 4031 is reversed, i.e., predominantly from theeaves of the roof towards the ridge.

FIG. 6 is comparable to FIG. 5 and illustrates highly schematically andnot to scale an a similar embodiment of the disclosed invention of abuilding with a similar cross section as in FIG. 5, here a type of gableroof (regardless of actual pitch). In addition to secondary compartment4031 in this embodiment there is an additional secondary compartment6032 predominantly between the primary compartment 200 and the ground.One particular mode of airflow within said secondary compartment 6032 isschematically illustrated.

Again, distributed throughout the inside of said building, and/or in oron its walls, and/or on the outside of said building, and/or in itsimmediate vicinity is a plurality of sensors 208, including in someversions of this embodiment sensor 2081 with wireless datacommunication. Again, said electronic controller 209 has been omitted inthis figure.

The illustration is highly schematic, and in particular the proportionsbetween the sensors 208 and the secondary compartments are exaggerated.It is not meant to imply that the sensors restrict the air flow in saidsecondary compartments.

FIG. 7 is comparable to FIG. 5 and illustrates highly schematically andnot to scale an embodiment of the disclosed invention of a building witha similar cross section as in FIG. 5, here a type of gable roof(regardless of actual pitch). In addition to secondary compartment 4031in this embodiment there are two additional secondary compartments 7032and 7033, predominantly alongside the side walls of the building,effectively encasing a large portion of the primary compartment 200. Insome such embodiments said secondary compartments 7032 and 7033 mayeffectively be created by at least partially hollow walls.

One particular mode of airflow within said secondary compartments isschematically illustrated. Clearly, depending on the direction in whichsaid actuators 207 and 2071 permit or drive air flow, variouscombinations are possible, in which direction air flow through theindividual secondary compartments can predominantly occur (resulting,among other physical effects, in differences in thermal gain or loss),which is precisely what said electronic controller 209 will determinebased on said ROM/SDNM in order to achieve at least one specific controltarget. Again, said electronic controller 209 has been omitted in thisfigure.

The illustration is highly schematic, and in particular the proportionsbetween the sensors 208 and the secondary compartments are exaggerated.It is not meant to imply that the sensors restrict the air flow in saidsecondary compartments.

FIG. 8 is comparable to FIG. 7 and illustrates highly schematically andnot to scale an embodiment of the disclosed invention of a building witha similar cross section as in FIG. 7, here a type of gable roof(regardless of actual pitch). However, in FIG. 7 the secondarycompartment 4031 comprised effectively the entire attic space, whereasin the embodiment shown in FIGS. 8a and 8b said secondary compartmentnow forms a smaller space 8031, which is predominantly located betweenan outer wall and an inner wall. In some such embodiments said secondarycompartment 8031 may effectively be created by at least partially hollowwalls. The advantage is that the attic space may become a primarycompartment 8003, which can be used for any of said primary purposes ofthe building.

Again, one particular mode of airflow within said secondary compartments8031, 7032, and 7033 is schematically illustrated. Clearly, depending onthe direction in which said actuators 207 and 2071 permit or drive airflow, various combinations are possible, in which direction air flowthrough the individual secondary compartments can occur (resulting,among other physical effects, in differences in thermal gain or loss),which is precisely what said electronic controller 209 will determinebased on said ROM/SDNM in order to achieve a specific control target inthe disclosed manner. Again, said electronic controller 209 has beenomitted in this figure.

The notable difference between FIGS. 8a and 8b is the presence ofadditional actuators 8073 and 8074 (functionally equivalent to either207 or 2071) close to the soffit of the roof, thus together with the twoproximate actuators forming a T-junction like shaped pathway (in somemodes similar a three-port valve), which permits a larger number ofpossible pathways, some of which can be beneficial.

Let's assume a building with at least at some locations a cross sectionsimilar to the one shown in FIG. 8b and that said actuators areprincipally placed in the illustrated manner. Let's furthermore assumethat there is a relatively high level of solar irradiance, also arrivingfrom a directions as shown (upper left), and that it is desirable toreduce the rate of increase in thermal budget (or stored thermal energy)of the primary compartment, which would result in an increase intemperature or would otherwise have to be countered by expendingsupplied energy to operate an AC system. Under such conditions it isdesirable to drive said actuators such that external air predominantlyis taken in on the shaded side, passing through secondary space 7033,then passing from the right side into said secondary compartments 8031.The actuators 8073 on the shaded (right) side may either be closed orpermit/support also partial inflow. The air then continues to the leftside of said secondary compartments 8031, which is predominantly exposedto solar irradiance. The actuators 207, which are located close to theridge are closed. The air then continues into secondary space 7032(actuators 8074 on the left side is also closed) and flows out throughactuator 207 at the bottom left side. Such a flow scheme will reduce therate with which thermal energy reaches said primary compartment as aresult of solar irradiance primarily from the left side. Thus, itreduces an increase in temperature and/or it reduces the requiredsupplied energy for an AC system. This is of course a highly simplifiedexample. What specifically the optimal values of in- or outflow rates atwhat time are is precisely what said controller will determine in thedisclosed manner.

Conversely, under conditions of again relatively high solar irradiancebut relatively low outside air temperature, i.e, when any or a morerapid increase in thermal energy with said primary compartment isdesirable, a flow in reverse as described above may be desirable,effectively moving thermal energy to the shaded (colder) side of thebuilding.

The illustration is highly schematic, and in particular the proportionsbetween the sensors 208 and the secondary compartments are exaggerated.It is not meant to imply that the sensors restrict the air flow in saidsecondary compartments.

FIG. 9 is comparable to FIG. 8 and illustrates highly schematically andnot to scale an embodiment of the disclosed invention of a building witha similar cross section as in FIG. 8, here a type of gable roof(regardless of actual pitch). Again, one particular mode of airflowwithin said secondary compartments 8031, 7032, and 7033 is schematicallyillustrated. Clearly, depending on the direction in which said actuators207 and 2071 permit or drive air flow, various combinations arepossible, in which direction air flow through the individual secondarycompartments can occur (resulting, among other physical effects, indifferences in thermal gain or loss), which is precisely what saidelectronic controller 209 will determine based on said ROM/SDNM in orderto achieve a specific control target in the disclosed manner. Theillustration is highly schematic, and in particular the proportionsbetween the sensors 208 and the secondary compartments are exaggerated.It is not meant to imply that the sensors restrict the air flow in saidsecondary compartments.

Furthermore, in this embodiment said at least one processing unit 2091has at least one human-machine interface comprising a display 9094and/or a keyboard 9095 (which in some embodiments may also be a touchscreen). In some embodiments there are options for voice basedinteractions with said at least one processing unit. In some embodimentsat least one processing unit 2091 may be connected to a computer networkused within said predominantly enclosed space and a person may useanother computer on said network to exchange date, including commands,with said at least one processing unit.

Furthermore, schematically shown is said at least one processing unit2091 of said control system 209 at least temporary achievingconnectivity to the internet and/or a cell network for mobile devices.In some such embodiments said control system 209 is directly connectedto the internet using an ethernet network already present in saidpredominantly enclosed space. In some embodiments said control system209 may further comprise or exchange data with at least one module 9096at least in part compatible with any wireless cellular network, or anyone of IS-95, IS-2000 (CDMA), EV-DO, GSM, EDGE, UMTS, LTE, HSPDA, WiMAX(IEEE 802.16), LIVID S/WiBAS, HiperMAN, HiperLAN, iBurst standards, or aradio-transmitter compatible with any future comparable such standard(incl. ‘5G’). As one specific example, USB GSM/3G/4G modems may serve assuch a module.

Thus, in some embodiments remote (or local) mobile devices such astelephones 9097, including so-called smart-phones, or other effectivelymobile computers, incl. so-called pads 9098, may be used to communicatewith said control system 209 either via the internet 9099 and/or amobile phone network, and/or any other communication at least partiallycomprising such forms of data exchange.

Clearly, these additional features in FIG. 9 are independent of theactual cross section and structure of the specific building and numberand shape of primary and secondary compartments

It shall be noted that the disclosed invention is applicable to a widevariety of predominantly enclosed spaces ranging from simple shacks,shelters, tents, containers, temporary or emergency housing units,mobile homes, trailer, or vans, to high-end energy-consumption optimizedvillas and other houses (incl. so called “zero-energy house”) in thefirst world. This also includes structures, which are being used forfabrication or storage of goods or equipment, including storage of food,garages, office buildings, compute centers (server farms), and evenhigh-rising buildings typically found in the center of modern cities.

Furthermore, the invention relates to any other predominantly enclosedspaces, which are exposed to electromagnetic radiation at least in theVIS and NIR wavelength range, as well as temporally varying levels ofambient air temperature and ambient air flow velocity and direction, andwherein it is desired to reduce temperature variations on the inside ofsaid predominantly enclosed spaces while minimizing or completelyeliminating the energy expenditure for required heating or cooling,and/or wherein it is desired to reduce the time to reach a desiredtemperature on the inside of said predominantly enclosed spaces, and/orwherein it is desired to increase the precision with which thetemperature inside said predominantly enclosed spaces can be controlled.

Traditionally, conventional indoor temperature and climate controlsystems of buildings are predominantly ‘reactive’ in the sense that theyoperate by activation and modulation of networked thermal energy sourcesand sinks in spaces based on thermostatic feedback, i.e. they compriseconventional control loops, which react to a deviation from a controltarget, after such a deviation occurs.

In contrast, in preferred embodiments of the disclosed invention saidcontrol system has sufficient data storage capacity and computationalpower to at least in part be able to execute an algorithm to achieve atleast one desired target. The disclosed control system posses aninternal model to anticipate thermal reactions of the building and toderive desirable control actions to achieve its at least one controltarget. In order to realize such a model-based control strategy, saidcontrol system incorporates a simplified virtual model, here referred asROM/SDNM of the building, which in some such embodiments runseffectively numerical simulation parallel to the building's actualphysical operation.

As mentioned above, the thermal behavior or the thermal budget ofpredominantly enclosed spaces, such as buildings or similar habitats, isa classic example of a highly complex multi-physics-problem, i.e., aproblem where numerous different physical effects or phenomena play arole in a coupled manner, i.e., simply put, in general the results of(any) one effect will have impact on the degree to which (any) anothereffect plays a role. As such, related (coupled) to the energy budget ofa building are the temperature distribution in the structure (walls) ofsaid building, as well as air flow (speed, direction), temperature andhumidity inside and within the direct vicinity of said building.(Subsequently, walls shall be understood to mean both vertical as wellas horizontal structures (i.e., floors and sealing) as well as any otherspatial orientation. Likewise, the envelope of a building shallsubsequently be understood to comprise any elements which define theoutside shape of a building, regardless of spatial orientation andregardless from which material they are made, for example including butnot limited to wall, windows, roofs, etc. and regardless if such adistinction is possible.)

The meaning of “thermal behavior” and “thermal budget” shall beunderstood to comprise at least:

-   -   the rate with which a building absorbs or emits energy    -   under given constant and/or time-dependent external and/or        internal loads,    -   (thus including the total and 3D spatial distribution of heat        capacity)    -   3D spatially and temporally resolved temperatures of bulk        materials and air    -   as a result of such constant and/or time-dependent external        and/or internal loads    -   the power (energy) required, i.e., to be provided or absorbed by        internal and/or external loads to keep at least bulk materials        and/or air of at least parts of a building within a certain        temperature range, and as a specific case    -   the power (energy) required, i.e., to be provided or absorbed by        internal loads to keep at least bulk materials and/or air of at        least parts of a building within a certain temperature range        under given function of or external time-dependent loads.

Some of the associated physical and numerical aspects will subsequentlybe discussed. One of the problems when modeling the thermal behavior ofa building is to accurately predict the above mentioned spatially andtemporally varying quantities for a given building and for givenexternal and/or internal loads. Load shall be understood to comprise anyfrom of energy source or sink. For example, internal loads can beheaters of any kind (e.g. an electric heater, gas burning oven etc.) oran air conditions system as an example of a sink. External loads areprimarily the external air flow field as well as solar irradiance.

As is well known, thermal energy (heat) Q [J] or [Ws] can be transferredby thermal conduction, convection, or electromagnetic radiation, alsoreferred to as “radiative thermal energy transfer” or “thermalradiation”, which typically refers to electromagnetic waves in the UV toFIR range. All these effects need to be considered in a high fidelitysimulation. Some underlying aspects will subsequently be brieflydiscussed.

Henceforth, electromagnetic irradiance, also referred to as radiativeflux, or radiant flux density, i.e., power per area, shall be denoted asΦ_(r)=P/A in [W·m⁻²]. Radiative thermal energy transfer is primarilygoverned by the following laws:

Planck's law describes the spectral distribution of the radiative flux,i.e., spectral radiance, an ideal black body emits as a function oftemperature and wavelength. Expressed in differential formdΦ _(r)(λ,T)=2πhc ²λ⁻⁵·(exp(hcλ ⁻¹ k ⁻¹ T ⁻¹)⁻¹ dλit gives the radiative power density per wavelength “slice”, whereinh=6.63·10⁻³⁴ Ws² is Planck's constant, c=3·10⁸ m/s is the velocity oflight, and k=1.38·10⁻²³ Ws/K is Boltzmann's constant.

(An approximation to Planck's law is Wien's law, here again indifferential form:dΦ _(r)(λ,T)=2πhc ²λ⁻⁵·(exp(hcλ ⁻¹ k ⁻¹  T ⁻¹))⁻¹ dλwhich somewhat underestimates spectral radiance at wavelength largerthan the wavelength of the maximum spectral radiance.)

We shall give a few examples for irradiance levels of ideal black bodiesat temperatures not uncommonly found on earth within the environment.For example, at T=293.1 K=20° C. the irradiance is Φ_(r)=412 W/m², at anonly 20 K higher temperature of T=313.1 K=40° C. it already increases toP=537 W/m² and at T=365.8 K=92.7° C. it reaches P≈1 kW/m².

However, at T=5780 K, the surface temperature of the sun, the radianceof an ideal black body reaches 62 MW/m². This extraordinary increase inpower emission efficiency with temperature is one of the reasons why thesun, at it's given size, can emit such an enormous power (≈4·10²⁶ W)that the solar irradiance at the average distance to earth, i.e. aboveearth' atmosphere, is about 1370 W/m², despite the large distance to thesun.

By integrating Planck's law over all wavelengths Stefan-Boltzmann's lawcan be derived, which makes more apparent this (highly non-linear)correlation between the temperature and the total radiated. i.e. emittedpower density (per area), i.e. radiative flux or irradiance, of an idealblack bodyΦ_(r) =σT ⁴with σ≈5.67·10⁻⁸ W m⁻² K⁻⁴ being the Stefan-Boltzmann constant.Furthermore noteworthy is that the lower the temperature of an object,the more is the spectral distribution of the emitted radiance shiftedtowards larger wavelength. The value of the wavelength where thespectral radiance has its maximum, as a function of temperature can bederived to beλ_(max)(T)=0.201·hcλ ⁻¹ k ⁻¹ T ⁻¹λ_(max)(T)=2.9·10⁻³ m/K·T ⁻¹

For example, at T=5780 K, the temperature of the surface of the sun,λ_(max)≈0.5 μm, whereas for example at the mentioned temperature ofT=365.8 K=92.7° C. the highest spectral irradiance is at approximatelyλ_(max)≈8 μm. At a room temperature of T=293.1 K=20° C. the maximum ofthe spectral radiance is at λ_(max)=9.9 μm.

To describe the reduced emitted power density of non-black bodies, anadditional dimensionless multiplicative factor, the spectral emissivitydε(T,λ) [0,1] is introduced. If integrated over all wavelengths, thisfactor represents the emissivity s relative to a perfect black body.Following Kirchhoff's law, we will here assume emissivity andabsorptivity dα (T,λ) (i.e., the ration of absorbed to incidentradiation, either per wavelength, or integrated over the consideredspectrum) to be effectively identical. Related to emissivity is spectralreflectivity, or integrated over al wavelength referred to just asreflectivity, which is given by (1−ε), or correspondingly (1−α)

Convective transfer of thermal energy is primarily energy transfer as aresult mass transfer of a fluid, here in particular of air flow. Thiscan be either forced convection (external, e.g. wind, or internal, e.g.due to the use of fans) or free or “natural” or “induced” convection(air flow) as a result buoyancy effects due to internal and/or externalair density differences as a result of temperature differences (e.g. asa result of local differences of the solar irradiance). Furthermoreconsidered must be induced air flow as a result of aerodynamic effects,e.g. whereby external flow can (cause dynamic) pressure differentials(Bernulli's principle, Venturi effect).

As already mentioned above, the three modes of thermal energy transfera) radiative energy transfer b) conductive thermal energy transfer, andc) convection (mass flow) are therefore three of the dominating physicalmechanisms (of numerous physical effects, which have influence on thethermal budget of a building, depending on a particular structure),which typically at least need to be considered in an High FidelityNumerical Model (HFNM) of the thermal behavior of a building since itpermits to obtain the resulting spatial distribution of stored thermalenergy and which is furthermore essential for thermal management asdisclosed.

The rate at which a building absorbs or emits energy is at least in partdetermined by any one or any combination of the following effects

-   -   radiative gains as a result of solar radiation or, typically to        a lesser degree,    -   thermal radiation emitted from surrounding surfaces    -   radiative losses of a building to the outside, particular under        conditions    -   of negligible solar input    -   thermal conduction of heat through solid or liquid portions of        the structure of a building (primarily walls including door and        windows, as well as roofs and floors). Liquid or liquid        crystalline structures may be present in reservoirs, pipes, or        other elements, which can be installed to enable increase of        thermal capacity and/or redistribution of thermal energy.

In order to assemble a reasonably accurate mathematical model of thethermal behavior of a building one needs to consider in a 3D spatiallyand temporally resolved manner the coupled effects of

-   -   externally imposed airflow (wind) and the resulting convective        thermal gains or losses,    -   radiative gains from solar energy and radiative losses if the        surfaces of buildings can emit toward colder surroundings (e.g.        the night sky),    -   induced air flow (outside as well as inside a building) as a        result of thermal gradients (both as a result of radiative gains        or other internal loads) and resulting redistribution of energy        as well as thermal gains or losses,    -   actively driven air flow (outside as well as inside a building)        and resulting redistribution of energy as well as thermal gains        or losses, and    -   any other heat source or sink within a building or its vicinity.

Again, these are in general all time- and spatially dependentthree-dimensional scalar or vector function. In principle, the basicequations which describe at least some of these phenomena are namely theNavier-Stokes equations, which describe fluid (air) flow and providetime- and spatially dependent fluid velocity, and pressure.

Navier Stokes equations are a system of nonlinear coupled partialdifferential equations, based on the assumptions that a fluid is acontinuous medium (i.e., the molecular nature can be ignored, which iscertainly true for air at the scale of buildings and atmosphericpressure), that the medium is a Newtonian fluid, and furthermore on thefollowing laws to be valid within the medium: conservation of mass,Newton's second law (conservation of momentum), conservation of energy,Fourier's law of heat conduction, and the existence of a state equationfor density, pressure, and temperature, and finally relationships forviscosity and thermal conductivity. A detailed discussion of theseequations is beyond the scope of the disclosed invention.

It is sufficient to realize that Navier-Stokes equations, whileessential to model the airflow, are numerically inherently difficult andcomputationally expensive to solve. Thus in some cases thesimplification of using only Euler equations may still provideacceptable results, which can be solve with somewhat less but stillconsiderable numerical effort.

Thermal conduction (e, g, the walls of a building) as result of a (ingeneral time-dependent) temperature gradient can be described byFourier's Law q_(n) (r, t)=−k (r)·A (r)·∂T/∂n(r, t) Again, bold lettersshall denote vector quantities. The flow of thermal energy, i.e., heatper time or heat flow rate q_(n)=Q/t [W] is a form of thermal power (ascalar), and hence heat flux (density) is given by q (r, t)=q_(n) (r,t)/A (r) [W/m²] is a form of power per area (through which it passes),which is given by the local thermal conductivity −k (r) [W/(m·K)]multiplied with the negative local temperature gradient −∂T/∂n(r, t)[K/m], and thus a vector.

Therefore, highly relevant for modeling the thermal behavior of abuilding is knowledge of the spatial distribution of the thermalconductivity k(r) of any bulk materials (this shall in a general sensealso include e.g. the equivalent thermal conductivity of multi-panewindows etc.) as well as the thermal conductivity of air. Typical valuesfor solids can range from about 1 W/(m·K) for some plastics and SiO₂glass to 380 W/(m·K) for copper at room temperature. Some foams can havethermal conductivity values of less than 0.1 W/(m·K), although these arenot real “solids”. Typical values for liquid range from about 0.2 to 10W/(m·K), for gases from 0.01 to 0.5 W/(m·K). The point is that relevantvalues range over several orders of magnitude, which makes obtainingvalid numerical solutions more difficult.

Beside knowledge of the spatial distribution of thermal conductivitywithin a building, the spatial distribution of heat capacity has to beknow, which describes the relationship between a change in temperatureand a change in thermal energy of an object (material). We willsubsequently denote any type of relative heat capacity with a small cand the total heat capacity (in the context of buildings sometimesreferred to a “thermal mass”) of an object with capital C [J/K].

As is well know, we distinguish between molar heat capacity c_(n) in[J/(mol·K)], i.e., heat capacity relative to the number of atoms ormolecules, specific heat capacity _(m)c_(p) in [J/(kg·K)], i.e., heatcapacity relative to mass, and volumetric heat capacity _(v)c_(p) in[J/(m³·K)] i.e., heat capacity relative to volume. Obviously, thevolumetric heat capacity of a substance can be derived from its specificheat capacity by multiplying it with its density ρ in [kg/m³]. These areisobaric heat capacity values, as indicated by the index p. It isinteresting to note that for most simple (mono-atomic) solids the molarheat capacity is approximately constant, as expressed by Dulongs-Petit'slawc _(n)≈3·R≈3·8.3J/(mol·K)=25J/(mol·K)

with R being the universal gas constant. There are of course significantdifferences with respect to specific and volumetric heat capacity. Thecombined influence of thermal conductivity k in [W/(m·K)] and volumetricheat capacity ρ ·c_(p) in [J/(m³·K)] is referred to as thermal inertia,or sometimes as thermal effusivity, and defined as e=(k·ρ ·c_(p))^(0.5).

Simulating the thermal behavior of a building comprises what is referredto as a conjugate heat transfer problem, since simultaneously solutionsto temperature distributions in solids as well as in a fluid arerequired, which further increases the numerical difficulty. (These typesof numerical problems are considered to be “μl-conditioned”.)

Thus it is Apparent that in Order to Describe the Thermal Behavior andAir Flow in an in the Vicinity of a Building, Time-Dependent Solutionsto Very Large Systems of Coupled Differential Equations are Required.

However, it is effectively impossible to find any direct analyticalsolution for these equations for any realistic 3D geometry (finite size,no or weak symmetry). At best, for some trivial, highly simplifiedabstract examples (usually 1D or 2D problems) analytical expressions infrom of approximations by (typically infinite) series of functions maybe found. Therefore, any serious and accurate analysis (prediction) ofthe thermal behavior of a building must be based on numerical models andnumerical solution methods to solve the underlying coupled differentialequations of a discretized model of at least one given building.

The more of said physical effects are incorporated into a mathematicalmodel, and the better (more accurately) material constants (orfunctions) are known, the more precisely such a model can predict thethermal behavior of the described building. Such models consist, atleast conceptually, of a potentially large set of coupled differentialequations and non-differential equations. (Conceptual in a sense that inorder to solve them they may never actually be explicitly written downsince one may start immediately with numerical or semi-numerical methodto obtain solutions, such method implicitly being based at least in parton said equations. See below.)

Creating such discretized models and obtaining the correspondingsolutions is difficult and computationally highly demanding, butpossible. In particular, typically any one or any combination of thefollowing numerical methods is used: Finite Element Method (FEM), FiniteDifference Method (FDM), Finite Volume Method (FVM), Monte Carlo Method,Boundary Element Method (BEM), often also in combination with iterativemethods including but not limited to successive approximations.

Regardless of the specific numerical method(s) one needs to know andconsider as input for a HFNM at least

-   -   the 3d spatial geometry of the building (i.e., shape of all        structural and other elements)    -   thus also providing enclosed air volumes,    -   the 3d spatial distribution of heat capacity of materials which        constitute a building    -   (enabeling also to compute the total heat capacity of a building        materials),    -   the 3d spatial distribution of thermal conductance (of bulk        material, including windows)    -   in a building,    -   the 3d spatial distribution of specific spectral electromagnetic        properties    -   (typically UV to FIR reflectivity) of bulk materials and        surfaces in a building,    -   the 3d spatial distribution of spectral electromagnetic        properties transmission of any    -   windows (i.e., transmittance/reflectance as function of        wavelength),    -   if present, the spatial distribution of phase change materials        within a building and the    -   corresponding phase transition enthalpies [J/kg],    -   if present, location, size, and parameters of other energy        sources or sinks (e.g. AC), and    -   if present, location, size, and parameters of actively driven        air.

A particular difficulty associated with obtaining the required solutionsarises from the fact that the HFNM has to consider numerous coupledphysical phenomena, including but not limited to surface and volumephenomena, as well as mass transport. For example, this may include butis typically not limited to consider buoyancy effects in many cases aspart of the analysis. Moreover, some components, such as fans, i.e.,actively driven flows, are themselves complicated numerical problems anddifficult to simulate from first principles. (Thus, fans can in someinstances be simplified as momentum sources and/or correspondingboundary conditions.) In addition, in some embodiments, which require aparticularly high level of accuracy, multiple (cascading) events ofsurfaces emitting and receiving electromagnetic radiation (UV to FIR)may be required to be considered within a HFNM.

Given the time constants of relevant effects in typical buildings, someof these phenomena must in many embodiments be treated as dynamic (ortransient), as opposed to steady-state, i.e. it can in general not beassumed that a building is in thermal steady state (although suchconditions can be reached). Moreover, temperature dependence of materialproperties, particular specific heat and/or emissivity will make theproblem nonlinear. In addition, any phase change in materialssignificantly contributes to a further increase in the level ofdifficulty. In such embodiments said walls comprise at least in part amaterial, which undergoes at least in part at least one phase change ofits molecular structure at a temperature which is between the minimumand maximum operating temperature (e.g. certain liquid crystals), aneffect than can be used for thermal energy storage.

As explained in more detail above (description of FIG. 3), once the HFNMhas been created, numerical simulations are executed several times.While some of the data required to generate the ROM/SDNM can be obtainedwith a single solution of said HFNM (e.g. computation of total heatcapacity), others will require several solution under changing boundaryand initial conditions, for example changing directions external airflow fields, i.e. time-dependent wind speeds and directions,time-dependent humidity levels, etc. as well as changing directions ofsolar irradiance (including e.g. also spectral shift, e.g. due to cloudand/or fog with varying degree of water content).

The obtained solution data for each simulation (i.e. specific solutionsof the HFNM for a specific set of boundary and initial conditions)include for example the time dependence of air temperatures in variouscompartments, time dependence of bulk and surface temperatures of wallsor other means of separating compartments (in general, there are ofcourse time-dependent 3d temperature profiles within all bulkmaterials).

Said solution data are being used to generate and refine said ROM/SDNM.The process of obtaining solutions to the HFNM is in some embodimentsrepeated in an iterative manner until the ROM/SDNM reaches an acceptablelevel of accuracy compared to the HFNM. It is helpful during this stepto know the location of said sensors 208 and 2081 as well as saidactuators 207 and 2071 and type of input data, since ultimately thesedata are the once which the ROM/SDNM will be given during futurepractical application to derive its control strategy from. Conversely,said iterative process can also serve to find desirable locations forsaid sensors and/or actuators. In other words, the measured sensory data_(m)M_(t), which form the input data for said ROM/SDNM, can beconsidered to cover relatively high-dimensional (parameter) space, andfor each specific vector _(m)M_(t) represents a specific state ofinternal and external conditions within this space, and for which theROM/SDNM must at least be able to provide the thermal system state S_(t)(or thermal budget) of said building (and the total stored thermalenergy Q_(t)) within a certain error margin.

For the purpose of this invention, the term “reduced order model” ROMshall be understood to comprise any method, which is able to derive,produce, successfully guess, or otherwise generate a set of linear andor nonlinear equations, which approximate the thermal behavior of apredominantly enclosed space, typically a building, but which arecomputationally less expensive to solve than the underlying differentialequations. In some embodiments deriving the ROM may comprise methodscomparable to those employed in various types of Design of Experiments(DOE), specifically also including Optimal Design of Experiments (ODOE).

For the purpose of this invention, the term “simplified discretenumerical model” (SDNM) shall also be understood to include a derivedsmaller (simpler) numerical model (e.g. a relatively small FEM model),which is numerically less expensive to solve (less main memory, lessfloating point operations) due to a reduced number of degrees of freedomand/or due to an optimized level of discretization (meshing), and/or useof higher order elements, which reduces the numerical problem size(typically sparse systems of linear equations) while maintaining anacceptable level of prediction accuracy.

This is based on recognizing that in several scenarios a veryconsiderable reduction in the number of elements and nodes (in case ofFEM) can be achieved, if nodes are placed at specific locations withinthe sold model. (In some embodiments finding such locations can be aniterative process, which in turn becomes part of the steps to beundertaken to generate the ROM/SDNM.)

In some embodiments one or more of such ROMs and SDNMs are combined tobe executed in said at least one “control system” or “electroniccontroller” 209, specifically within said processing unit 2091 to derivecontrol signals for said actuators 207 which at least approximate anyone or any combination of system targets of reducing the average energyexpenditure for keeping at least one primary compartment of a buildingwithin a desired temperature range by means of active air conditioning,or reducing temperature variations during a typical 24-hour cycle withinsaid at least one primary compartment of said building, or reducing oneor both of the average temperature or the peak temperature of said atleast one primary compartment of said building.

One of the distinct benefits of the disclosed invention of deriving andusing ROMs/SDNMs for subsequent system control of the thermal budget isthat the required computations can be executed on (by today's and futurestandards) small computers and/or controllers (in terms of there DRAMsize and FLOPS), i.e., on relatively inexpensive hardware systems.Predictions of the thermal budget and control strategy decisions can becomputed in some embodiments in fractions of seconds, if ROMs/SDNMs areused, compared to hours or days for solutions of the underlying fullscale HFNM. The continued decline on price for a given level of computeperformance will further strengthen this aspect.

This benefit of the disclosed invention shall be further illustrated bytwo technical analogies.

By way of a first analogy, during (SCUBA) diving the human body absorbsnitrogen in blood and tissue depending on the depth profile of the dive,which needs to be gradually released (at shallower depth) to avoiddecompression sickness. Originally, relative simple dive tables weredeveloped and are still being used as guidelines, which provide roughlythe required decompression times after exposure to a specific (constant)dive depth for a specific dive time. In reality, most dives are notexecutes by staying at a one specific depth for most of the dive,instead a diver will desirably follow an arbitrary depth profile, thusabsorbing (and releasing) nitrogen at varying rates. What makes thisproblem complicated is the fact that the human body is of course a verycomplex and in general a continuous system (or in this context a gasabsorber) wherein various organs, tissues, fluids, etc have varyingabsorption coefficients. Thus, a high fidelity prediction of theabsorbed amount of nitrogen and the required decompression time wouldrequired a 3d numeric model of (a typical or specific) human body (i.e.,the entire geometry of all relevant organs) spatially discretized withsufficient resolution and assuming all “material” properties are known.

However, it was eventually realized (major contributions by Albert A.Bülmann) that as a sufficiently good approximation the human body can interms of nitrogen absorption and release (correspondingly for othergases) be represented by a finite (and relatively small) number ofdiscrete (imaginary) compartments (16 compartments given by Bülmann),for which absorption rates (some times given as half-times) are know.(The electric equivalent would be a network of 16 series RC-circuits.)Thus the problem of computing the nitrogen load as a result of anarbitrary dive profile can be reduced to (a sum of) one-dimensionalnumerical integrations. This is something a modern battery poweredmicroprocessor can easily do, thus, enabling the dive compute. (Manymodels are e.g. based on a Bülmann ZHL-12 or ZHL-16 algorithm, dependingon how many compartments are considered.) It is noteworthy that this isnowadays for a digital computer a negligible computational effort, butit was still a considerable challenge during the development of thefirst digital dive computers in the mid 70's. Even earlier attempts tobuild a dive computer based on effectively mechanical-pneumatic elements(essentially making it an analog computers) were generally not verysuccessful.

By way of another analogy this is comparable to generating a schematicof an electronic circuit, which is a simplified model describing themore complex physical processes, which occur in each electronic element,such as transistors, diodes, logic gate, or even more complex subunitssuch as operational amplifiers, each of which are represented in asimulation of said electronic circuit as at least one mathematicalfunction, which approximately represent the typically complex physicaleffects in each said element. Thus, solutions to the behavior of theelectronic circuit (which from a physical standpoint is a 3dconglomerate of copper, doped silicon, silicon oxide, other metals,etc.) can be obtained with much less computational effort compared toattempting to create and solve a numerical method of the underlyingphysical effects. (In microelectronics R&D this is typically referred toas device simulation, e.g. to numerically predict the performance of atransistor based on knowledge about shape, size and distribution ofdopant levels in the used semiconductor material(s).)

Getting back to the disclosed inventions, similarly a building doesabsorb and release thermal energy at least as a result of

-   -   a) the “exposure profile” to solar irradiance (as a function of        direction and time), wind speed (as a function of direction and        time), air temperature (as a function of time), air humidity (as        a function of time), etc.,    -   b) active internal energy sources or sinks (e.g. ovens or AC        systems), and    -   c) changes in air flow in said secondary compartments.

The advantage of using ROMs/SDNMs of the underlying physics is that saidcontroller 209 can assess the thermal budget of a specific building andmake prediction with comparatively little computational effort and canderive desirable control strategies on how to drive said actuators 207.

While in general the thereby derived control/drive signals for saidactuators will be relatively complicated functions (also depending onthe number of secondary compartments, the number of actuators etc.) afew trivial examples shall be given to further illustrate some of thebenefits of the disclosed invention.

Let's assume a building with at some locations a cross section similarto the one shown in FIG. 8b and that said actuators are principallyplaced in the illustrated manner. Let's furthermore assume that there isa relatively high level of solar irradiance, also arriving from adirections as shown (upper left), and that it is desirable to reduce therate of increase in thermal budget (or stored thermal energy) of theprimary compartment, which would result in an increase in temperature orwould have otherwise to be countered by expending supplied energy tooperate an AC system. Under such conditions it is desirable to drivesaid actuators such that external air predominantly is taken in on theshaded side, passing through secondary space 7033, then passing from theright side into said secondary compartments 8031. The actuators 8073 onthe shaded (right) side may either be closed or permit/support alsopartial inflow. The air then continues to the left side of saidsecondary compartments 8031, which is predominantly exposed to solarirradiance. The actuators 207, which are located close to the ridge areclosed. The air then continues into secondary space 7032 (actuators 8074on the left side is also closed) and flows out through actuator 207 atthe bottom left side. Such a flow will reduce the rate with whichthermal energy reaches said primary compartment as a result of solarirradiance primarily from the left side. Thus it reduces an increase intemperature and/or it reduces the required supplied energy for any ACsystem. This is of course a highly simplified example. What specificallythe optimal values of in- or outflow rates at what time are is preciselywhat said controller will determine in the disclosed manner.

Conversely, under conditions of again relatively high solar irradiancebut relatively low outside air temperature, i.e, when any or a morerapid increase in thermal energy with said primary compartment isdesirable, a flow in reverse as described above may be desirable,effectively moving thermal energy to the shaded (colder) side of thebuilding.

In some embodiments the generation and/or refinement of said ROM/SDNMmay be also supported by executing measurements of the thermal budget onan actual similar (or even identical) building, i.e. it is measured howthe thermal budget reacts to varying external and/or internal loads andother environmental conditions, thereby providing additional data pointto create and or refine said ROM/SDNM. In some embodiments thegeneration and/or refinement of said ROM/SDNM may be predominantly doneby executing measurements of the thermal budget on the actual or similar(or even identical) building.

In some embodiments the disclosed invention will have other oradditional benefits such as reducing the long-term consumption ofbuilding materials (and related expenses) by increasing the intervalbetween required repairs, specifically for materials made at least inpart from wood and/or other organic materials. This can be achieved byincluding as control target for example to maintain certain humiditylevels and/or temperature levels in said secondary compartments, whichin some embodiments will reduce aging (or decay) of at least some partsof wooden structures, if present. In such embodiments said controller209 may for example preferentially permitted air flow in said secondarycompartments under conditions of relatively low humidity of the externalair and suppressed or reduced air flow under conditions of relativelyhigh humidity, based on data from said sensors 208.

Thus, in some embodiments said at least one electronic controller 209 isalso executing at least one algorithm, either entirely in softwareand/or at least partially in hardware (e.g. in FPGAs), which at least inpart serves to at least approximate any one or any combination of systemtargets of

-   -   reducing the average expenditure of at least one resource within        one both of        -   at least one primary compartment of a building or        -   at least one secondary compartment of a building.

Thus, in some embodiments said at least one electronic controller 209 isalso executing an at least one algorithm, either entirely in softwareand/or at least partially in hardware (e.g. in FPGAs), which at least inpart serves to at least approximate any one or any combination of systemtargets of

-   -   affecting in at least one secondary compartment on average and        within a certain numeric range a certain amount of air        throughput and said air being within another certain numeric        range of a certain humidity level,    -   or    -   affecting in at least one secondary compartment on average and        within a certain numeric range a certain amount of air        throughput and said air having within at least one other certain        numeric range of at least one chemical or physical property.        There are Several Preferable Embodiments with Respect to Said        Control System.

The processing unit 2091 of said control system 207 may be based on anyone or any combination of suitable computational architecture, incl. forexample ARM as well as x86, x86-64 (Intel, AMD, VIA) based systems, inparticular embedded system modules, single board computers, or boardswith Micro-ATX, Mini-ITX, Nano-ITX, or Pico-ITX (VIA Technologies) formfactor, any embedded systems, furthermore any so called “system on achip” (SoC) e.g. Snapdragon, and may in some embodiments at leastpartially also comprise FPGAs and/or PLCs. The chassis and/or busstructure of said processing unit 2091 may in some embodiments be basedon PCI, PXI, PXIe.

To give a few additional specific examples, this may in some embodimentscomprise hardware based on Ardunio Mega/Uno/Yun/Zero, Banana Pi,BeagleBone Black/X15, ESP8266, Jetson TK1 (Nvidia), Raspberry Pi 2/Zerosystems (ARM CPU based), and more on the higher end e.g. Jetson TX1(Nvidia).

While the prediction of directional chance of solar irradiance isrelatively simple (and entirely possible without real time input intothe controller), in some embodiments said control system mayelectronically receive weather forecast data, which it uses to calculateestimates of expected future changes to the energy budget of saidbuilding, and wherein such estimates are used to enhance the performanceof said control system. In some such embodiments said control system mayreceive said weather forecast data via an at least temporarilyestablished internet connection. For example, expected times of chancein solar irradiance e.g. as a result of clouds to further can be used toenhance its control strategy.

In some embodiments said control system has sufficient data storagecapacity and computational power to be at least in part based on analgorithm to achieve at least one desired target, and to also retainpreviously obtained signals and/or data corresponding to such signals,subsequently also referred to as ‘historic data’, obtained from at leastone of said sensors, and uses said historic data to improved over timeits performance. In some such embodiments said data also comprisehistoric performance data, i.e. data, which are at least in some degreea measure how well the control system performed. A measure forperformance may in some embodiments be e.g. how precisely or quickly adesired targeted temperature on the inside of said predominantlyenclosed space has been reached, for how long a certain temperaturerange could by maintained, or how much additional supplied energy, e.g.in form of electricity or gas, had to be used to maintain such atemperature range. In other words, said control systems improves itsperformance by learning form previous, accumulated experience. In somesuch embodiments said control system may use such historic data toenhance or correct said ROMs/SDNMs, i.e. it may correct or fine-tunecertain parameters of ROMs/SDNMs, in other words said control systemlearns over time to better predict the response to certain inputs (e.g.solar radiation) and to its own actions, and thus improves its controlstrategy accordingly. In some such embodiments said control system mayretain such historic data ranging from a few days to a few years, inparticular including complete seasonal cycles. In some such embodimentssaid control system may retain such historic data during its entirelifetime.

In some additional such embodiments such collected historic data (sensordata, performance data, reduced order model data), in particularincluding complete seasonal cycles, are collected by a first controlsystem on one specific building, and are later provided to and stored ina single or plurality of other (typically new) control systems, whichwill control a similar building. In other words said control systemincorporates learning experience previously obtained by similar controlsystems e.g. on similar buildings.

In some embodiments said control system is at least temporarily beingconnected to the internet and provides any one or any combination of thefollowing services comprising: In some such embodiments said controlsystem is sending status and performance data per email. In some suchembodiments said control system enables remote log-ins to display statusand performance data on a remote computer or a remote mobile device. Insome such embodiments said control system enables remote log-ins tomanipulate the operation of said control system, including to changecontrol target data, from a remote computer or a remote mobile device,including in particular from a so-called smart phone or so-calledwearable device.

In some embodiments said control systems from a plurality of buildingsare at least temporarily connected to the internet, and are providingany one or any combination of the following services comprising: In somesuch embodiments said control systems from a plurality of buildings areat least temporarily connecting to a common web site, and aretransmitting status and/or performance data. In some such embodimentssaid web site enables user log-ins to said control systems of specifichouses belonging to said plurality of houses, from another plurality ofinternet connected computers or a remote mobile devices, including inparticular from a so-called smart phones or so-called wearable devices,and said web site enables displaying status and performance data, onsaid other plurality of internet connected computers, or remote mobiledevices.

In some such embodiments said web site enables remote manipulation ofthe operation of any one of said control systems belonging to saidplurality of houses, including changing the control target data, fromsaid other plurality of internet connected computers or a remote mobiledevices, including in particular from a so-called smart phones orso-called wearable devices

Within the context of the disclosed invention, ‘web site’ shall beunderstood to also include any internet connected computer, or group ofcomputers, including virtual machines or other dynamically assignedcomputers or computing resources depending on load conditions,addressable typically via IP address or URL, which can receive and senddata by any protocols and on various ports, but such data may at leastin part comprise data, which are in general not necessarily humanreadable, or the data may not necessarily be html or other formatsinterpretable by a regular internet browser to display human readabletext or numbers (as would be the case for regular html based web sites).

In some embodiments said control systems from a plurality of buildingsare at least temporarily connected to the internet and perform any oneor any combination of the following services comprising: In some suchembodiments said control systems from a plurality of buildings are atleast temporarily connecting to a common web site, or to anotherinternet connected computer at least partially acting as a server, andare transmitting any one or any combination of control system statusdata, and/or energy consumption data, and/or thermal budget data, and/orcontrol system status performance data, and/or local solar radiationdata, and/or local air temperature data, and/or local air speed data,and/or local air humidity data.

In some such embodiments said web site predominantly automaticallyanalyzes said data received at least from some of said control systemsbelonging to said plurality of houses, and/or manipulates the operationof at least some of said control systems belonging to said plurality ofhouses, including changing control target data. In combination withabove disclosed learning mode, said common web site or server mayanalyze environmental and performance data from several control systemsto improve the average performance of said control systems, and byproviding said control systems with updates of the required parameters,and/or reduced order models, and/or code, and/or algorithm.

In some embodiments said control system is at least temporarilyconnected to a mobile phone network and provides at least temporarilyany one or any combination of the following services comprising: In somesuch embodiments said control system is sending status and performancedata per sms. In some such embodiments said control system is enablingvoice and/or touch-tone controlled remote log-ins, and/or providingspoken status and performance data via computer generated voice. In somesuch embodiments said control system is enabling voice and/or touch-tonecontrolled remote log-ins to manipulate via voice and/or touch-tone theoperation of said control system, including to change control targetdata, and provides spoken feedback of such manipulations via computergenerated voice.

Types of System Buses and Communication

In some embodiments the data communication between said at least oneelectronic controller, and at least some of said sensors and/or actuator(both of which themselves in some embodiments comprise electroniccontrollers, typically micro controllers) is at least in part based onwired standard and/or protocols as described in/by/under: 1-wire,ARCNET, BACnet, CAN, CANopen, C-Bus, DALI, DMX512, DOLLx8, Ethernet,EtherCAT, (or any other Ethernet based communications systems), FlexRay,GPIB, I²C, Insteon, Instabus, INTERBUS, KNX, LIN, LonTalk/LonWorks, OPC,OpenWebNet, Profibus, PSIS, S-Bus (“Smart-Bus”), SENT, SDI-12, SIOX,SMBus, SMI, RS-232, RS-485 (incl. “Advanced RS-485, or any other variantor successor”, RS-422, SCADA, SafetyBUS, SERCOS, Sinec H1, USB, or othertypes of networks and field buses or future derived versions thereof, orother future comparable standards and/or protocols. In some embodimentsexisting power lines (typically 110V-230V) are at least in part used totransmit information between said at least one electronic controller andsaid sensors and/or actuators, including but not limited to X10,Universal Powerline Bus (UPB), EN 50090, European Home Systems Protocol(EHS), PLCBUS, or any future derived versions thereof, or other futurecomparable standards and/or protocols.

In some embodiment the data communication between said at least oneelectronic controller, and at least some of said sensors and/or actuator(both of which themselves in some embodiments comprise electroniccontrollers, typically micro controllers), and in some embodiments alsoat least in part (optionally) the required power supply thereof, is atleast in part based on one or both of

-   -   a) wireless standards and/or protocols, in particular any type        of (relatively) low-rate wireless personal area network        (LR-WPANs), and    -   b) wireless standards and/or protocols covering low power wide        area networks (LP-WAN)        including but not limited to those based on IEEE 805.15.1        (Bluetooth, incl. Bluetooth Low Energy), Wireless USB, IEEE        802.15.4, ITU-T G.9959, 6LoWPAN, ANT, ANT+, DASH7, EnOcean,        Insteon, KNX-RF, LTE-Cat M, LoRaWan, MiWi, MiWi P2P, MyraNed,        nWave, RPMA, SigFox, Thread (protocol), Weightless-W,        Weightless-N, Weightless-P, WirelessHART, XMPP, ZigBee, Z-Wave,        or any future derived versions thereof, or other future        comparable standards and/or protocols.

In some such embodiments the data communication is established betweensaid at least one electronic controller from multiple, proximallylocated buildings.

In some embodiment the data communication between said at least oneelectronic controller, and at least some of said sensors and/or actuatoris at least in part based on wireless standards and/or protocols, inparticular any type of medium or higher rate wireless personal areanetwork, which in many instances may already be present in manybuildings, including but not limited to those based all variants of IEEE802.11 (“Wi-Fi”), IEEE 802.16m (“WiMAX”), and/or any other TCP/IP (IPv4and/or IPv6) based local wireless networks, and/or any derived versionsthereof, or other future comparable standards and/or protocols.

In some such embodiments the data communication is established betweensaid at least one electronic controller from multiple, proximallylocated buildings.

In some embodiment the data communication between said at least oneelectronic controller, and at least some of said sensors and/or actuatoris at least in part based on optical transport networks (“opticalfibers”), including passive optical networks (PON), and related standardand/or protocols as described ITU-T G.709, G.798, G.872, G.983, G.984,G.987, as well as IEEE Ethernet PON, or future derived versions thereof,or other future comparable standards and/or protocols.

The increasing automation of homes, besides providing novelfunctionality and convenience, poses also increased security risks byenabling (unintended) access to vital functions of a building as well asunderlying data, including the possibility of manipulating or otherwiseexploiting the same. Thus, in particular, in some embodiment the datacommunication between said electronic controller, and at least some ofsaid sensors and or actuator does incorporate various means to protectthe communication from eavesdropping and/or manipulation by externalattackers by various means, including but not limited to encryption andauthentication mechanisms. (Or at least make such attacks more difficultand/or expensive.)

There are Several Preferable Embodiments with Respect to the Materialfrom which Said Walls 201 and 204 are Made.

Wall shall be understood to mean any physical means for enclosure sincenot in all cases and design a distinction between a roof and a wall maybe possible.

In some embodiments said walls comprise masonry (incl. but not limitedto bricks and tiles).

In some embodiments said walls comprise concrete.

In some embodiments said walls comprise cementitious material.

In some embodiments said walls comprise metal.

In some embodiments said walls comprise wood.

In some embodiments said walls comprise wood and some materialpredominantly serving as thermal insulation.

In some embodiments said walls comprise plastic.

In some embodiments said walls comprise a fiber-reinforced polymer.

In some embodiments said walls comprise glass.

In some embodiments said walls comprise metal and glass.

In some embodiments said walls comprise at least in part a material,which undergoes at least in part at least one phase change of itsmolecular structure at a temperature which is between the minimum andmaximum operating temperature.

In some embodiments nano- and micro-particles from populations withpredominantly distinct size distributions, shape distributions, chemicalcompositions, crystal structures, and crystallinity distributions areadded to materials or constitute materials, from which walls 201 and/or204 are made, and any one or any combination of effective volumetricheat capacity, latent heat, and heat conductivity of said thermalcarrier liquid is modified compared to base properties of the purematerials.

There are Several Preferable Embodiments with Respect AdditionalElements and Coatings on at Least Parts of the Outside of Said Building.

In some embodiments at least some of the outside facing surfaces of saidbuilding may be made from materials or have at least partially coatingmade from material, which at least in part are based on tailored mixesof nano- and micro particles (and/or cavities). In some embodiments atleast some of the outside facing parts of the envelope of said building,and or associated surfaces, may be made from materials or have at leastpartially coating made from materials, which at least in part are basedon tailored mixes of nano- and micro particles (and/or cavities).

In some embodiments at least some of the outside facing parts of theenvelope of said building, and or associated surfaces, may have certain(non-black and non-white) colors or patterns in the VIS range and veryhigh NIR reflectivity. Such reflective properties may be achieved byusing coatings or bulk materials, which are at least in part are basedon tailored mixes of nano- and micro particles (and/or cavities) toapproximate a desired spectral reflectivity.

In some embodiments at least some of the outside facing parts of theenvelope of said building, and or associated surfaces, typically atleast those facing south, may have broadband super-reflective propertiesat least in the VIS and NIR wavelength range, either due to applyingadditional layers or by using bulk materials, which are at least in partbased on the use of tailored mixtures of populations of nano- and/ormicro particles and/or cavities with distinct properties per population.

In some embodiments the amount absorbed energy as a result exposure todirectionally and temporarily varying levels of solar irradiance can bemodulated by placing in the relative proximity of at least parts of saidbuilding a plurality of spatially adjustable functional elements, whichan be used to chance the portion of incident solar irradiance, whichreaches outside facing surfaces of sid building, in particular thesurfaces of said walls 201 and 204. At least those areas are preferablycovered, which are predominantly directly exposed to said solarradiation.

Spatially adjustable, or a spatial degree of freedom, shall mean thatsaid plurality of functional elements are mounted such that there is atleast one translational or rotational degree of freedom. In someembodiments this may be a single rotational degree of freedom around ahorizontal or vertical axis, such as for example the hinge-like element.In some embodiments there may be two rotational degrees of freedomwhereas in other embodiments there may be one rotational and onetranslational degree of freedom. In yet some other embodiments saidfunctional elements may also be able to change their shape.

In some embodiments said functional elements can be metallic, ceramic(incl. glass, clay, minerals, or concrete), or plastic (or other polymerbased synthetic materials), and/or multi-layered composites of suchmaterials. Said elements have generally one spatial dimension with issignificantly smaller than the two others. The placement of saidfunctional elements is such that thermally conductive bridges to theinner shell via direct contact are relatively small or effectivelynegligible.

In some embodiments said functional elements can be at least in partmade from bulk materials or at least partially coated with materials,which are at least in part are based on tailored mixes of nano- andmicro particles (and/or cavities) to approximate a desired spectralreflectivity in any one or any combination of the UV, VIS, and IRwavelength range.

In some embodiments existing buildings such as single family homes,apartment buildings, or any other existing buildings, are retrofittedwith one or any combination of elements of the disclosed invention.

Headings are included herein for reference and to aid in locatingvarious sections. These headings are not intended to limit the scope ofthe concepts described with respect thereto. Such concepts may haveapplicability throughout the entire specification.

The previous description of the disclosed implementations is provided toenable any person skilled in the art to make or use the presentinvention. Various modifications to these implementations will bereadily apparent to those skilled in the art, and the generic principlesdefined herein may be applied to other implementations without departingfrom the spirit or scope of the invention. Thus, the present inventionis not intended to be limited to the implementations shown herein but isto be accorded the widest scope consistent with the principles and novelfeatures disclosed herein.

While the above description has pointed out novel features of theinvention as applied to various embodiments, the skilled person willunderstand that various omissions, substitutions, and changes in theform and details of the device or process illustrated may be madewithout departing from the scope of the invention.

What is claimed is:
 1. A method of controlling air flow for a building,comprising: providing a control system, the control system comprising acomputational model of a thermal behavior of a building, wherein thecomputational model comprises at least one of: a reduced order model;and a simplified discrete numerical model; receiving an input of adesired system target into the control system, wherein the desiredsystem target comprises at least one of: a reduced average energyexpenditure for keeping at least one primary compartment of a buildingwithin a desired temperature range by means of active air conditioning;a reduced temperature variation during a typical 24-hour cycle withinsaid at least one primary compartment of a building; a reduced averagetemperature of said at least one primary compartment of a building; anda reduced peak temperature of said at least one primary compartment of abuilding; receiving an electronic signal into the control system from atleast one sensor; and modulating air flow to and from the secondarycompartment to approximate the desired system target, based upon themodel, the input, and the electronic signal.
 2. The method according toclaim 1, further comprising: storing data with the control system,wherein the data comprises one or more of: past signals from at leastone of said sensors; and past data corresponding to a system controlperformance; and using the data to at least approximate one or more of:changing parameters of; changing a logic structure of; and improving aprediction accuracy of the computational model, and based thereonimproving at least on average system control performance.
 3. The methodaccording to claim 2 further comprising: connecting said control systemto one or more of the internet and a wireless cellular network; andperforming one or more of the following with the control system:exchanging data with other computers connected to said networks; sendingstatus and performance data; receiving one or both of control data andother performance supporting data; enabling remote log-ins to displaystatus and performance data on a remote computer or a remote mobiledevice; enabling remote log-ins to manipulate operation of said controlsystem, including to change control target data from a remote computeror remote mobile devices; enabling data exchange with and remote controlof said control system from mobile devices at least in part based onsending and receiving one or both of sms and email; enabling one or moreof voice or touch-tone controlled remote log-ins to manipulate via oneor more of voice or touch-tone operation of said control system,including to change control target data; and providing spoken feedbackof said manipulations via computer generated voice.
 4. The methodaccording to claim 3 further comprising: connecting a plurality of thecontrol systems corresponding with a plurality of buildings to theinternet, and further comprising one or more of: connecting to at leastone common internet connected computer and transmitting one or more ofstatus and performance data; connecting to at least one common internetconnected computer and enabling user log-ins to said control systems ofspecific houses belonging to said plurality of houses, from anotherplurality of internet connected computers or remote mobile devices;connecting to at least one common internet connected computer to enablestatus and performance data to be displayed on said other plurality ofinternet connected computers or remote mobile devices; and connecting toat least one common internet connected computer to enable remotemanipulation of operation of at least one of said control systemsbelonging to said plurality of houses, including changing control targetdata, from said other plurality of internet connected computers orremote mobile devices.
 5. The method according to claim 3 furthercomprising: connecting a plurality of the control systems correspondingwith a plurality of buildings to the internet, and further comprisingone or more of: connecting to at least one common internet connectedcomputer and transmitting one or more of: control system status data;energy consumption data; thermal budget data; control system statusperformance data; local solar radiation data; local air temperaturedata; and local air humidity data; and automatically performing, atleast partially with the at least one common internet connectedcomputer, one or more of: analyzing data received from at least some ofsaid control systems corresponding with said plurality of houses; andmanipulating operation of at least some of said control systemscorresponding with said plurality of houses, including changing controltarget data.
 6. The method according to claim 3 further comprising:electronically receiving weather forecast data with said at least onecontrol system, wherein the data are used at least in part for one ormore of: calculating estimates of expected future changes to an energybudget of said building; changing parameters of the model used in saidcontrol system; changing the model type used in said control system; atleast on average enhancing predictive performance of said model used insaid control system; and at least on average enhancing performance ofsaid control system.
 7. The method according to claim 3 furthercomprising: electronically receiving data to at least a first of saidcontrol systems of a first building, the data originating from othercontrol systems corresponding with a plurality of other buildings,wherein the plurality of other buildings are predominantly in at leastone of: a same area as the first building and a same type of buildingwith respect to each other, wherein said received data comprises any oneor more of: control system status data; control system model type;control system model parameters; control system performance data; energyconsumption data; thermal budget data; local solar radiation data; localair temperature data; and local air humidity data; and using suchreceived data for one or more of: calculating estimates of expectedfuture changes to an energy budget of said first building; changingparameters of the computational model used in said first control system;changing the computational model type used in said first control system;at least on average enhancing predictive performance of saidcomputational model used in said first control system; and at least onaverage enhancing performance of said first control system.
 8. Themethod according to claim 3, wherein the at least one sensor comprisesat least one sensor in the group consisting of: at least one sensor toprovide electronic signals representing solar radiation levels; at leastone sensor to provide electronic signals representing ambient airtemperature levels; and at least one sensor to provide electronicsignals representing air temperature in said at least one secondarycompartment.
 9. The method according to claim 3, wherein modulatingcomprises one or more of: modulating the throughput of passive air flowto and from said at least secondary compartment; modulating the averagespeed of passive air flow to and from said at least secondarycompartment; modulating the throughput of actively driven air flow toand from said at least secondary compartment; and modulating the averagespeed of actively driven air flow to and from said at least secondarycompartment.
 10. The method according to claim 2 further comprising:connecting a plurality of the control systems corresponding with aplurality of buildings to the internet, and further comprising one ormore of: connecting to at least one common internet connected computerand transmitting one or more of status and performance data; connectingto at least one common internet connected computer and enabling userlog-ins to said control systems of specific houses belonging to saidplurality of houses, from another plurality of internet connectedcomputers or remote mobile devices; connecting to at least one commoninternet connected computer to enable status and performance data to bedisplayed on said other plurality of internet connected computers orremote mobile devices; and connecting to at least one common internetconnected computer to enable remote manipulation of operation of atleast one of said control systems belonging to said plurality of houses,including changing control target data, from said other plurality ofinternet connected computers or remote mobile devices.
 11. The methodaccording to claim 2 further comprising: connecting a plurality of thecontrol systems corresponding with a plurality of buildings to theinternet, and further comprising one or more of: connecting to at leastone common internet connected computer and transmitting one or more of:control system status data; energy consumption data; thermal budgetdata; control system status performance data; local solar radiationdata; local air temperature data; and local air humidity data; andautomatically performing, at least partially with the at least onecommon internet connected computer, one or more of: analyzing datareceived from at least some of said control systems corresponding withsaid plurality of houses; and manipulating operation of at least some ofsaid control systems corresponding with said plurality of houses,including changing control target data.
 12. The method according toclaim 2 further comprising: electronically receiving weather forecastdata with said at least one control system, wherein the data are used atleast in part for one or more of: calculating estimates of expectedfuture changes to an energy budget of said building; changing parametersof the model used in said control system; changing the model type usedin said control system; at least on average enhancing predictiveperformance of said model used in said control system; and at least onaverage enhancing performance of said control system.
 13. The methodaccording to claim 2 further comprising: electronically receiving datato at least a first of said control systems of a first building, thedata originating from other control systems corresponding with aplurality of other buildings, wherein the plurality of other buildingsare predominantly in at least one of: a same area as the first buildingand a same type of building with respect to each other, wherein saidreceived data comprises any one or more of: control system status data;control system model type; control system model parameters; controlsystem performance data; energy consumption data; thermal budget data;local solar radiation data; local air temperature data; and local airhumidity data; and using such received data for one or more of:calculating estimates of expected future changes to an energy budget ofsaid first building; changing parameters of the computational model usedin said first control system; changing the computational model type usedin said first control system; at least on average enhancing predictiveperformance of said computational model used in said first controlsystem; and at least on average enhancing performance of said firstcontrol system.
 14. The method according to claim 2, wherein the atleast one sensor comprises at least one sensor in the group consistingof: at least one sensor to provide electronic signals representing solarradiation levels; at least one sensor to provide electronic signalsrepresenting ambient air temperature levels; and at least one sensor toprovide electronic signals representing air temperature in said at leastone secondary compartment.
 15. The method according to claim 2, whereinmodulating comprises one or more of: modulating the throughput ofpassive air flow to and from said at least secondary compartment;modulating the average speed of passive air flow to and from said atleast secondary compartment; modulating the throughput of activelydriven air flow to and from said at least secondary compartment; andmodulating the average speed of actively driven air flow to and fromsaid at least secondary compartment.
 16. The method according to claim1, further comprising: connecting said control system to one or more ofthe internet and a wireless cellular network; and performing one or moreof the following with the control system: exchanging data with othercomputers connected to said networks; sending status and performancedata; receiving one or both of control data and other performancesupporting data; enabling remote log-ins to display status andperformance data on a remote computer or a remote mobile device;enabling remote log-ins to manipulate operation of said control system,including to change control target data from a remote computer or remotemobile devices; enabling data exchange with and remote control of saidcontrol system from mobile devices at least in part based on sending andreceiving one or both of sms and email; enabling one or more of voice ortouch-tone controlled remote log-ins to manipulate via one or more ofvoice or touch-tone operation of said control system, including tochange control target data; and providing spoken feedback of saidmanipulations via computer generated voice.
 17. The method according toclaim 16 further comprising: connecting a plurality of the controlsystems corresponding with a plurality of buildings to the internet, andfurther comprising one or more of: connecting to at least one commoninternet connected computer and transmitting one or more of status andperformance data; connecting to at least one common internet connectedcomputer and enabling user log-ins to said control systems of specifichouses belonging to said plurality of houses, from another plurality ofinternet connected computers or remote mobile devices; connecting to atleast one common internet connected computer to enable status andperformance data to be displayed on said other plurality of internetconnected computers or remote mobile devices; and connecting to at leastone common internet connected computer to enable remote manipulation ofoperation of at least one of said control systems belonging to saidplurality of houses, including changing control target data, from saidother plurality of internet connected computers or remote mobiledevices.
 18. The method according to claim 16 further comprising:connecting a plurality of the control systems corresponding with aplurality of buildings to the internet, and further comprising one ormore of: connecting to at least one common internet connected computerand transmitting one or more of: control system status data; energyconsumption data; thermal budget data; control system status performancedata; local solar radiation data; local air temperature data; and localair humidity data; and automatically performing, at least partially withthe at least one common internet connected computer, one or more of:analyzing data received from at least some of said control systemscorresponding with said plurality of houses; and manipulating operationof at least some of said control systems corresponding with saidplurality of houses, including changing control target data.
 19. Themethod according to claim 16 further comprising: electronicallyreceiving weather forecast data with said at least one control system,wherein the data are used at least in part for one or more of:calculating estimates of expected future changes to an energy budget ofsaid building; changing parameters of the model used in said controlsystem; changing the model type used in said control system; at least onaverage enhancing predictive performance of said model used in saidcontrol system; and at least on average enhancing performance of saidcontrol system.
 20. The method according to claim 16 further comprising:electronically receiving data to at least a first of said controlsystems of a first building, the data originating from other controlsystems corresponding with a plurality of other buildings, wherein theplurality of other buildings are predominantly in at least one of: asame area as the first building and a same type of building with respectto each other, wherein said received data comprises any one or more of:control system status data; control system model type; control systemmodel parameters; control system performance data; energy consumptiondata; thermal budget data; local solar radiation data; local airtemperature data; and local air humidity data; and using such receiveddata for one or more of: calculating estimates of expected futurechanges to an energy budget of said first building; changing parametersof the computational model used in said first control system; changingthe computational model type used in said first control system; at leaston average enhancing predictive performance of said computational modelused in said first control system; and at least on average enhancingperformance of said first control system.
 21. The method according toclaim 16, wherein the at least one sensor comprises at least one sensorin the group consisting of: at least one sensor to provide electronicsignals representing solar radiation levels; at least one sensor toprovide electronic signals representing ambient air temperature levels;and at least one sensor to provide electronic signals representing airtemperature in said at least one secondary compartment.
 22. The methodaccording to claim 16, wherein modulating comprises one or more of:modulating the throughput of passive air flow to and from said at leastsecondary compartment; modulating the average speed of passive air flowto and from said at least secondary compartment; modulating thethroughput of actively driven air flow to and from said at leastsecondary compartment; and modulating the average speed of activelydriven air flow to and from said at least secondary compartment.
 23. Themethod according to claim 1 further comprising: connecting a pluralityof the control systems corresponding with a plurality of buildings tothe internet, and further comprising one or more of: connecting to atleast one common internet connected computer and transmitting one ormore of status and performance data; connecting to at least one commoninternet connected computer and enabling user log-ins to said controlsystems of specific houses belonging to said plurality of houses, fromanother plurality of internet connected computers or remote mobiledevices; connecting to at least one common internet connected computerto enable status and performance data to be displayed on said otherplurality of internet connected computers or remote mobile devices; andconnecting to at least one common internet connected computer to enableremote manipulation of operation of at least one of said control systemsbelonging to said plurality of houses, including changing control targetdata, from said other plurality of internet connected computers orremote mobile devices.
 24. The method according to claim 1 furthercomprising: connecting a plurality of the control systems correspondingwith a plurality of buildings to the internet, and further comprisingone or more of: connecting to at least one common internet connectedcomputer and transmitting one or more of: control system status data;energy consumption data; thermal budget data; control system statusperformance data; local solar radiation data; local air temperaturedata; and local air humidity data; and automatically performing, atleast partially with the at least one common internet connectedcomputer, one or more of: analyzing data received from at least some ofsaid control systems corresponding with said plurality of houses; andmanipulating operation of at least some of said control systemscorresponding with said plurality of houses, including changing controltarget data.
 25. The method according to claim 1 further comprising:electronically receiving weather forecast data with said at least onecontrol system, wherein the data are used at least in part for one ormore of: calculating estimates of expected future changes to an energybudget of said building; changing parameters of the model used in saidcontrol system; changing the model type used in said control system; atleast on average enhancing predictive performance of said model used insaid control system; and at least on average enhancing performance ofsaid control system.
 26. The method according to claim 1 furthercomprising: electronically receiving data to at least a first of saidcontrol systems of a first building, the data originating from othercontrol systems corresponding with a plurality of other buildings,wherein the plurality of other buildings are predominantly in at leastone of: a same area as the first building and a same type of buildingwith respect to each other, wherein said received data comprises any oneor more of: control system status data; control system model type;control system model parameters; control system performance data; energyconsumption data; thermal budget data; local solar radiation data; localair temperature data; and local air humidity data; and using suchreceived data for one or more of: calculating estimates of expectedfuture changes to an energy budget of said first building; changingparameters of the computational model used in said first control system;changing the computational model type used in said first control system;at least on average enhancing predictive performance of saidcomputational model used in said first control system; and at least onaverage enhancing performance of said first control system.
 27. Themethod according to claim 1, wherein the at least one sensor comprisesat least one sensor in the group consisting of: at least one sensor toprovide electronic signals representing solar radiation levels; at leastone sensor to provide electronic signals representing ambient airtemperature levels; and at least one sensor to provide electronicsignals representing air temperature in said at least one secondarycompartment.
 28. The method according to claim 1, wherein the at leastone sensor comprises: at least one sensor to provide electronic signalsrepresenting solar radiation levels; at least one sensor to provideelectronic signals representing ambient air temperature levels; and atleast one sensor to provide electronic signals representing airtemperature in said at least one secondary compartment.
 29. The methodaccording to claim 1, wherein modulating comprises one or more of:modulating the throughput of passive air flow to and from said at leastsecondary compartment; modulating the average speed of passive air flowto and from said at least secondary compartment; modulating thethroughput of actively driven air flow to and from said at leastsecondary compartment; and modulating the average speed of activelydriven air flow to and from said at least secondary compartment.
 30. Themethod according to claim 1 wherein said at least one secondarycompartment comprises a wall comprising at least one material thatundergoes at least one phase change of its molecular structure at atemperature which is between a minimum and maximum operating temperaturewithin said secondary compartment.
 31. The method according to any oneof claims 2, 16, 3, 23, 24, 25, 26 and 1 wherein said at least onesecondary compartment comprises at least one material that undergoes atleast one phase change of its molecular structure at a temperature whichis between a minimum and maximum operating temperature within saidsecondary compartment.
 32. The method according to any one of claims 2,16, 3, 23, 24, 25, 26 and 1 wherein at least some outside facing partsof the envelope of said building comprise materials, the materialscomprising at least some tailored mixes of nano- and micro particlescavities.
 33. The method according to any one of claims 2, 16, 3, 23,24, 25, 26 and 1, wherein at least some outside facing surfaces of saidbuilding comprise materials, the materials comprising at least sometailored mixes of nano- and micro particles and/or cavities, and whichhave certain non-black and non-white colors or patterns in a Visible(VIS) wavelength range and very high Near Infrared (NIR) reflectivity.